SIGGRAPH 2021: Technical Papers
Technical Papers Chair:
Jury Member(s):
- Yagiz Aksoy
- Sheldon Andrews
- Nicolas Bonneel
- Duygu Ceylan
- Fanny Chevalier
- Angela Dai
- Abe Davis
- Tali Dekel
- Matthew Fisher
- Hongbo Fu
- Abhijeet Ghosh
- Ioannis Gkioulekas
- Sehoon Ha
- Eric Heitz
- Philipp Herholz
- Nicolas Holzschuch
- Ruizhen Hu
- Hui Huang
- Qixing Huang
- Angjoo Kanazawa
- Min H. Kim
- Kiriakos N. Kutulakos
- David N. Levin
- Tzu-Mao Li
- Jing Liao
- Miles Macklin
- Marcus A. Magnor
- Maud Marchal
- Manuel M. Oliveira
- Daniel Ritchie
- Ana Serrano
- Melina Skouras
- Shuran Song
- Laura Waller
- Sai-Kit Yeung
- Ersin Yumer
Overview:
Scientists and researchers present the latest advancements that drive the industry, inspire new work, and ignite memorable discussions.
Papers:
Sort By
Title
Presenter
3D weaving with curved ribbons
Presenter(s):
[Ren]
[Panetta]
[Chen]
[Isvoranu]
[Poincloux]
[Brandt]
[Martin]
[Pauly]
[SIGGRAPH 2021]
A fitted radiance and attenuation model for realistic atmospheres
Presenter(s):
[Wilkie]
[Vévoda]
[Bashford-Rogers]
[Hosek]
[Iser]
[Kolářová]
[Rittig]
[Křivánek]
[SIGGRAPH 2021]
A gradient-based framework for 3D print appearance optimization
Presenter(s):
[Nindel]
[Iser]
[Rittig]
[Wilkie]
[Křivánek]
[SIGGRAPH 2021]
A mathematical foundation for foundation paper pieceable quilts
Presenter(s):
[Leake]
[Bernstein]
[Davis]
[Agrawala]
[SIGGRAPH 2021]
A momentum-conserving implicit material point method for surface tension with contact angles and spatial gradients
Presenter(s):
[Chen]
[Kala]
[Marquez-Razon]
[Gueidon]
[Hyde]
[Teran]
[SIGGRAPH 2021]
A non-exponential transmittance model for volumetric scene representations
Presenter(s):
[Vicini]
[Jakob]
[Kaplayan]
[SIGGRAPH 2021]
A perceptual model for eccentricity-dependent spatio-temporal flicker fusion and its applications to foveated graphics
Presenter(s):
[Krajancich]
[Kellnhofer]
[Wetzstein]
[SIGGRAPH 2021]
A time-independent deformer for elastic contacts
Presenter(s):
[Brunel]
[Bénard]
[Guennebaud]
[SIGGRAPH 2021]
A unified second-order accurate in time MPM formulation for simulating viscoelastic liquids with phase change
Presenter(s):
[Su]
[Xue]
[Han]
[Jiang]
[Aanjaneya]
[SIGGRAPH 2021]
Acorn: adaptive coordinate networks for neural scene representation
Presenter(s):
[Martel]
[Lindell]
[Lin]
[Chan]
[Monteiro]
[Wetzstein]
[SIGGRAPH 2021]
AgileGAN: stylizing portraits by inversion-consistent transfer learning
Presenter(s):
[Song]
[Luo]
[Liu]
[Ma]
[Lai]
[Zheng]
[Cham]
[SIGGRAPH 2021]
AMP: adversarial motion priors for stylized physics-based character control
Presenter(s):
[Peng]
[Ma]
[Abbeel]
[Levine]
[Kanazawa]
[SIGGRAPH 2021]
An inverse method for the exploration of layered material appearance
Presenter(s):
[Bati]
[Barla]
[Pacanowski]
[SIGGRAPH 2021]
An unbiased ray-marching transmittance estimator
Presenter(s):
[Kettunen]
[d’Eon]
[Pantaleoni]
[Novák]
[SIGGRAPH 2021]
Antithetic sampling for Monte Carlo differentiable rendering
Presenter(s):
[Zhang]
[Dong]
[Doggett]
[Zhao]
[SIGGRAPH 2021]
Authoring consistent landscapes with flora and fauna
Presenter(s):
[Ecormier-Nocca]
[Cordonnier]
[Carrez]
[Moigne]
[Memari]
[Benes]
[Cani]
[SIGGRAPH 2021]
Beyond blur: real-time ventral metamers for foveated rendering
Presenter(s):
[Walton]
[Dos Anjos]
[Friston]
[Swapp]
[Akşit]
[Steed]
[Ritschel]
[SIGGRAPH 2021]
Bijective and coarse high-order tetrahedral meshes
Presenter(s):
[Jiang]
[Zhang]
[Hu]
[Schneider]
[Zorin]
[Panozzo]
[SIGGRAPH 2021]
Bistable auxetic surface structures
Presenter(s):
[Chen]
[Panetta]
[Schnaubelt]
[Pauly]
[SIGGRAPH 2021]
Boundary-sampled halfspaces: a new representation for constructive solid modeling
Presenter(s):
[Du]
[Zhou]
[Carr]
[Ju]
[SIGGRAPH 2021]
Capturing detailed deformations of moving human bodies
Presenter(s):
[Chen]
[Park]
[Macit]
[Kavan]
[SIGGRAPH 2021]
ChoreoMaster: choreography-oriented music-driven dance synthesis
Presenter(s):
[Chen]
[Tand]
[Lei]
[Zhang]
[Guo]
[Zhang]
[Hu]
[SIGGRAPH 2021]
Coarse-to-fine: facial structure editing of portrait images via latent space classifications
Presenter(s):
[Wu]
[Yang]
[Xiao]
[Jin]
[SIGGRAPH 2021]
Computational design of weingarten surfaces
Presenter(s):
[Pellis]
[Kilian]
[Pottmann]
[Pauly]
[SIGGRAPH 2021]
Computational inverse design of surface-based inflatables
Presenter(s):
[Panetta]
[Isvoranu]
[Chen]
[Siéfert]
[Roman]
[Pauly]
[SIGGRAPH 2021]
Consistent depth of moving objects in video
Presenter(s):
[Zhang]
[Cole]
[Tucker]
[Freeman]
[Dekel]
[SIGGRAPH 2021]
Constrained projective dynamics: real-time simulation of deformable objects with energy-momentum conservation
Presenter(s):
[Kee]
[Um]
[Jeong]
[Han]
[SIGGRAPH 2021]
Constrained willmore surfaces
Presenter(s):
[Soliman]
[Chern]
[Diamanti]
[Knöppel]
[Pinkall]
[Schröder]
[SIGGRAPH 2021]
Control strategies for physically simulated characters performing two-player competitive sports
Presenter(s):
[Won]
[Gopinath]
[Hodgins]
[SIGGRAPH 2021]
DAG amendment for inverse control of parametric shapes
Presenter(s):
[Michel]
[Boubekeur]
[SIGGRAPH 2021]
Deep relightable appearance models for animatable faces
Presenter(s):
[Bi]
[Lombardi]
[Saito]
[Simon]
[Wei]
[Mcphail]
[Ramamoorthi]
[Sheikh]
[Saragih]
[SIGGRAPH 2021]
DeepFaceEditing: deep face generation and editing with disentangled geometry and appearance control
Presenter(s):
[Chen]
[Liu]
[Lai]
[Rosin]
[Li]
[Fu]
[Gao]
[SIGGRAPH 2021]
DeepFormableTag: end-to-end generation and recognition of deformable fiducial markers
Presenter(s):
[Yaldiz]
[Meuleman]
[Jang]
[Ha]
[Kim]
[SIGGRAPH 2021]
Designing actuation systems for animatronic figures via globally optimal discrete search
Presenter(s):
[Huber]
[Poranne]
[Coros]
[SIGGRAPH 2021]
Designing an encoder for StyleGAN image manipulation
Presenter(s):
[Tov]
[Alaluf]
[Nitzan]
[Patashnik]
[Cohen-Or]
[SIGGRAPH 2021]
DiffAqua: a differentiable computational design pipeline for soft underwater swimmers with shape interpolation
Presenter(s):
[Ma]
[Du]
[Zhang]
[Wu]
[Spielberg]
[Katzschmann]
[Matusik]
[SIGGRAPH 2021]
Direct delta mush skinning compression with continuous examples
Presenter(s):
[Le]
[Villeneuve]
[Gonzalez-Ochoa]
[SIGGRAPH 2021]
Discovering diverse athletic jumping strategies
Presenter(s):
[Yin]
[Yang]
[Panne]
[Yin]
[SIGGRAPH 2021]
Discrete conformal equivalence of polyhedral surfaces
Presenter(s):
[Gillespie]
[Springborn]
[Crane]
[SIGGRAPH 2021]
Displaced signed distance fields for additive manufacturing
Presenter(s):
[Brunton]
[Rmaileh]
[SIGGRAPH 2021]
Driving-signal aware full-body avatars
Presenter(s):
[Bagautdinov]
[Wu]
[Simon]
[Prada]
[Shiratori]
[Wei]
[Xu]
[Sheikh]
[Saragih]
[SIGGRAPH 2021]
Dynamic closest color warping to sort and compare palettes
Presenter(s):
[Kim]
[Choi]
[SIGGRAPH 2021]
Editable free-viewpoint video using a layered neural representation
Presenter(s):
[Zhang]
[Liu]
[Ye]
[Zhao]
[Zhang]
[Wu]
[Zhang]
[Yu]
[Xu]
[SIGGRAPH 2021]
Eliminating topological errors in neural network rotation estimation using self-selecting ensembles
Presenter(s):
[Xiang]
[SIGGRAPH 2021]
End-to-end complex lens design with differentiate ray tracing
Presenter(s):
[Sun]
[Wang]
[Fu]
[Dun]
[Heidrich]
[SIGGRAPH 2021]
Endless loops: detecting and animating periodic patterns in still images
Presenter(s):
[Halperin]
[Hakim]
[Vantzos]
[Hochman]
[Benaim]
[Sassy]
[Kupchik]
[Bibi]
[Fried]
[SIGGRAPH 2021]
Fast diffraction pathfinding for dynamic sound propagation
Presenter(s):
[Schissler]
[Mückl]
[Calamia]
[SIGGRAPH 2021]
Fast linking numbers for topology verification of loopy structures
Presenter(s):
[Qu]
[James]
[SIGGRAPH 2021]
Fast quasi-harmonic weights for geometric data interpolation
Presenter(s):
[Wang]
[Solomon]
[SIGGRAPH 2021]
Fire in paradise: mesoscale simulation of wildfires
Presenter(s):
[Hädrich]
[Banuti]
[Palubicki]
[Pirk]
[Michels]
[SIGGRAPH 2021]
Foldover-free maps in 50 lines of code
Presenter(s):
[Garanzha]
[Kaporin]
[Kudryavtseva]
[Protais]
[Ray]
[Sokolov]
[SIGGRAPH 2021]
FovVideoVDP: a visible difference predictor for wide field-of-view video
Presenter(s):
[Mantiuk]
[Denes]
[Chapiro]
[Kaplayan]
[Rufo]
[Bachy]
[Lian]
[Patney]
[SIGGRAPH 2021]
Free-form scanning of non-planar appearance with neural trace photography
Presenter(s):
[Ma]
[Kang]
[Zhu]
[Wu]
[Zhou]
[SIGGRAPH 2021]
Fusion 360 gallery: a dataset and environment for programmatic CAD construction from human design sequences
Presenter(s):
[Willis]
[Pu]
[Luo]
[Chu]
[Du]
[Lambourne]
[Solar-Lezama]
[Matusik]
[SIGGRAPH 2021]
General virtual sketching framework for vector line art
Presenter(s):
[Mo]
[Simo-Serra]
[Gao]
[Zou]
[Wang]
[SIGGRAPH 2021]
Geometry and tool motion planning for curvature adapted CNC machining
Presenter(s):
[Barton]
[Bizzarri]
[Rist]
[Sliusarenko]
[Pottmann]
[SIGGRAPH 2021]
Guaranteed globally injective 3D deformation processing
Presenter(s):
[Fang]
[Li]
[Jiang]
[Kaufman]
[SIGGRAPH 2021]
Guaranteed-quality higher-order triangular meshing of 2D domains
Presenter(s):
[Mandad]
[Campen]
[SIGGRAPH 2021]
Hierarchical neural reconstruction for path guiding using hybrid path and photon samples
Presenter(s):
[Zhu]
[Xu]
[Sun]
[Kuznetsov]
[Meyer]
[Jensen]
[Su]
[Ramamoorthi]
[SIGGRAPH 2021]
High-order differentiable autoencoder for nonlinear model reduction
Presenter(s):
[Shen]
[Yang]
[Shao]
[Wang]
[Jiang]
[Lan]
[Zhou]
[SIGGRAPH 2021]
Highlight-aware two-stream network for single-image SVBRDF acquisition
Presenter(s):
[Guo]
[Lai]
[Tao]
[Cai]
[Wang]
[Guo]
[Yan]
[SIGGRAPH 2021]
HodgeNet: learning spectral geometry on triangle meshes
Presenter(s):
[Smirnov]
[Solomon]
[SIGGRAPH 2021]
Incompressible flow simulation on vortex segment clouds
Presenter(s):
[Xiong]
[Tao]
[Zhang]
[Feng]
[Zhu]
[SIGGRAPH 2021]
Interactive modelling of volumetric musculoskeletal anatomy
Presenter(s):
[Abdrashitov]
[Bang]
[Levin]
[Singh]
[Jacobson]
[SIGGRAPH 2021]
Interactive Monte Carlo denoising using affinity of neural features
Presenter(s):
[Işık]
[Mullia]
[Fisher]
[Eisenmann]
[Gharbi]
[SIGGRAPH 2021]
Intersection-free rigid body dynamics
Presenter(s):
[Ferguson]
[Li]
[Schneider]
[Ureta]
[Langlois]
[Jiang]
[Zorin]
[Kaufman]
[Panozzo]
[SIGGRAPH 2021]
Kelvin transformations for simulations on infinite domains
Presenter(s):
[Nabizadeh]
[Ramamoorthi]
[Chern]
[SIGGRAPH 2021]
Knit sketching: from cut & sew patterns to machine-knit garments
Presenter(s):
[Kaspar]
[Wu]
[Luo]
[Makatura]
[Matusik]
[SIGGRAPH 2021]
KnitKit: a flexible system for machine knitting of customizable textiles
Presenter(s):
[Nader]
[Quek]
[Chia]
[Weeger]
[Yeung]
[SIGGRAPH 2021]
Knitting 4D garments with elasticity controlled for body motion
Presenter(s):
[Liu]
[Han]
[Zhang]
[Chen]
[Lai]
[Doubrovski]
[Whiting]
[Wang]
[SIGGRAPH 2021]
Learning a family of motor skills from a single motion clip
Presenter(s):
[Lee]
[Lee]
[Lee]
[Lee]
[SIGGRAPH 2021]
Learning active quasistatic physics-based models from data
Presenter(s):
[Srinivasan]
[Wang]
[Rojas]
[Klár]
[Kavan]
[Sifakis]
[SIGGRAPH 2021]
Learning an animatable detailed 3D face model from in-the-wild images
Presenter(s):
[Feng]
[Feng]
[Black]
[Bolkart]
[SIGGRAPH 2021]
Learning contact corrections for handle-based subspace dynamics
Presenter(s):
[Romero]
[Casas]
[Rodríguez]
[Otaduy]
[SIGGRAPH 2021]
Learning meaningful controls for fluids
Presenter(s):
[Chu]
[Thuerey]
[Seidel]
[Theobalt]
[Zayer]
[SIGGRAPH 2021]
Learning skeletal articulations with neural blend shapes
Presenter(s):
[Zhang]
[Aberman]
[Hanocka]
[Liu]
[Sorkine-Hornung]
[Chen]
[SIGGRAPH 2021]
Learning time-critical responses for interactive character control
Presenter(s):
[Lee]
[Min]
[Lee]
[Lee]
[SIGGRAPH 2021]
Low-cost SPAD sensing for non-line-of-sight tracking, material classification and depth imaging
Presenter(s):
[Callenberg]
[Shi]
[Heide]
[Hullin]
[SIGGRAPH 2021]
ManipNet: neural manipulation synthesis with a hand-object spatial representation
Presenter(s):
[Zhang]
[Ye]
[Shiratori]
[Komura]
[SIGGRAPH 2021]
Mechanics-aware deformation of yarn pattern geometry
Presenter(s):
[Sperl]
[Narain]
[Wojtan]
[SIGGRAPH 2021]
Medial IPC: accelerated incremental potential contact with medial elastics
Presenter(s):
[Lan]
[Yang]
[Kaufman]
[Yao]
[Li]
[Jiang]
[SIGGRAPH 2021]
Mixture of volumetric primitives for efficient neural rendering
Presenter(s):
[Lombardi]
[Simon]
[Schwartz]
[Zollhoefer]
[Sheikh]
[Saragih]
[SIGGRAPH 2021]
MoCap-solver: a neural solver for optical motion capture data
Presenter(s):
[Chen]
[Wang]
[Zhang]
[Xu]
[Zhang]
[Hu]
[SIGGRAPH 2021]
MOCCA: modeling and optimizing cone-joints for complex assemblies
Presenter(s):
[Wang]
[Song]
[Pauly]
[SIGGRAPH 2021]
Modeling and fabrication with specified discrete equivalence classes
Presenter(s):
[Liu]
[Zhang]
[Zhang]
[Ye]
[Liu]
[Fu]
[SIGGRAPH 2021]
Monte Carlo estimators for differential light transport
Presenter(s):
[Zeltner]
[Speierer]
[Georgiev]
[Jakob]
[SIGGRAPH 2021]
Multiscale cholesky preconditioning for ill-conditioned problems
Presenter(s):
[Chen]
[Schäfer]
[Huang]
[Desbrun]
[SIGGRAPH 2021]
NeuMIP: multi-resolution neural materials
Presenter(s):
[Kuznetsov]
[Mullia]
[Xu]
[Hasan]
[Ramamoorthi]
[SIGGRAPH 2021]
Neural animation layering for synthesizing martial arts movements
Presenter(s):
[Starke]
[Zhao]
[Zinno]
[Komura]
[SIGGRAPH 2021]
Neural complex luminaires: representation and rendering
Presenter(s):
[Zhu]
[Bai]
[Xu]
[Bako]
[Velázquez-Armendáriz]
[Wang]
[Sen]
[Hasan]
[Yan]
[SIGGRAPH 2021]
Neural monocular 3D human motion capture with physical awareness
Presenter(s):
[Shimada]
[Golyanik]
[Xu]
[Perez]
[Theobalt]
[SIGGRAPH 2021]
Neural scene graph rendering
Presenter(s):
[Granskog]
[Schnabel]
[Rousselle]
[Novák]
[SIGGRAPH 2021]
Only a matter of style: age transformation using a style-based regression model
Presenter(s):
[Alaluf]
[Patashnik]
[Cohen-Or]
[SIGGRAPH 2021]
Optimizing UI layouts for deformable face-rig manipulation
Presenter(s):
[Kim]
[Singh]
[SIGGRAPH 2021]
Orienting point clouds with dipole propagation
Presenter(s):
[Metzer]
[Hanocka]
[Zorin]
[Giryes]
[Panozzo]
[Cohen-Or]
[SIGGRAPH 2021]
Pareto gamuts: exploring optimal designs across varying contexts
Presenter(s):
[Makatura]
[Guo]
[Schulz]
[Solomon]
[Matusik]
[SIGGRAPH 2021]
Path replay backpropagation: differentiating light paths using constant memory and linear time
Presenter(s):
[Vicini]
[Speierer]
[Jakob]
[SIGGRAPH 2021]
Path-space differentiable rendering of participating media
Presenter(s):
[Zhang]
[Yu]
[Zhao]
[SIGGRAPH 2021]
PH-CPF: planar hexagonal meshing using coordinate power fields
Presenter(s):
[Pluta]
[Edelstein]
[Vaxman]
[Ben-Chen]
[SIGGRAPH 2021]
PhotoApp: photorealistic appearance editing of head portraits
Presenter(s):
[R.]
[Tewari]
[Dib]
[Weyrich]
[Bickel]
[Seidel]
[Pfister]
[Matusik]
[Elgharib]
[Theobalt]
[SIGGRAPH 2021]
Physical validation of simulators in computer graphics: a new framework dedicated to slender elastic structures and frictional contact
Presenter(s):
[Romero]
[Ly]
[Rasheed]
[Charrondière]
[Lazarus]
[Neukirch]
[Bertails-Descoubes]
[SIGGRAPH 2021]
QuanTaichi: a compiler for quantized simulations
Presenter(s):
[Hu]
[Liu]
[Yang]
[Xu]
[Kuang]
[Xu]
[Dai]
[Freeman]
[Durand]
[SIGGRAPH 2021]
Real-time 3D neural facial animation from binocular video
Presenter(s):
[Cao]
[Agrawal]
[Torre]
[Chen]
[Saragih]
[Simon]
[Sheikh]
[SIGGRAPH 2021]
Real-time deep dynamic characters
Presenter(s):
[Habermann]
[Liu]
[Xu]
[Zollhoefer]
[Pons-Moll]
[Theobalt]
[SIGGRAPH 2021]
Real-time locally injective volumetric deformation
Organizer(s):
[Liao]
[Chen]
[Hua]
[Liu]
[Weber]
[SIGGRAPH 2021]
Real-time neural radiance caching for path tracing
Presenter(s):
[Müller]
[Rousselle]
[Novák]
[Keller]
[SIGGRAPH 2021]
Reliable feature-line driven quad-remeshing
Presenter(s):
[Pietroni]
[Nuvoli]
[Alderighi]
[Cignoni]
[Tarini]
[SIGGRAPH 2021]
Revisiting integration in the material point method: a scheme for easier separation and less dissipation
Presenter(s):
[Fei]
[Wu]
[SIGGRAPH 2021]
ROSEFusion: random optimization for online dense reconstruction under fast camera motion
Presenter(s):
[Zhang]
[Zhu]
[Zheng]
[Xu]
[SIGGRAPH 2021]
SANM: a symbolic asymptotic numerical solver with applications in mesh deformation
Presenter(s):
[Jia]
[SIGGRAPH 2021]
Scalable image-based indoor scene rendering with reflections
Presenter(s):
[Xu]
[Wu]
[Zu]
[Huang]
[Yang]
[Bao]
[Xu]
[SIGGRAPH 2021]
Seamless manga inpainting with semantics awareness
Presenter(s):
[Xie]
[Xia]
[Li]
[Wong]
[SIGGRAPH 2021]
ShapeMOD: macro operation discovery for 3D shape programs
Presenter(s):
[Jones]
[Charatan]
[Guerrero]
[Mitra]
[Ritchie]
[SIGGRAPH 2021]
Solid-fluid interaction with surface-tension-dominant contact
Presenter(s):
[Ruan]
[Liu]
[Zhu]
[Sueda]
[Wang]
[Chen]
[SIGGRAPH 2021]
SP-GAN: sphere-guided 3D shape generation and manipulation
Presenter(s):
[Li]
[Li]
[Hui]
[Fu]
[SIGGRAPH 2021]
StrokeStrip: joint parameterization and fitting of stroke clusters
Presenter(s):
[Van Mossel]
[Liu]
[Vining]
[Bessmeltsev]
[Sheffer]
[SIGGRAPH 2021]
StyleCariGAN: caricature generation via StyleGAN feature map modulation
Presenter(s):
[Jang]
[Ju]
[Jung]
[Yang]
[Tong]
[Lee]
[SIGGRAPH 2021]
Surface multigrid via intrinsic prolongation
Presenter(s):
[Liu]
[Zhang]
[Ben-Chen]
[Jacobson]
[SIGGRAPH 2021]
SWAGAN: a style-based wavelet-driven generative model
Presenter(s):
[Gal]
[Hochberg]
[Bermano]
[Cohen-Or]
[SIGGRAPH 2021]
Swept volumes via spacetime numerical continuation
Presenter(s):
[Sellán]
[Aigerman]
[Jacobson]
[SIGGRAPH 2021]
Systematically differentiating parametric discontinuities
Presenter(s):
[Bangaru]
[Michel]
[Mu]
[Bernstein]
[Li]
[Ragan-Kelley]
[SIGGRAPH 2021]
The effect of shape and illumination on material perception: model and applications
Presenter(s):
[Serrano]
[Chen]
[Wang]
[Piovarči]
[Seidel]
[Didyk]
[Myszkowski]
[SIGGRAPH 2021]
The shape matching element method: direct animation of curved surface models
Presenter(s):
[Trusty]
[Chen]
[Levin]
[SIGGRAPH 2021]
Thin-film smoothed particle hydrodynamics fluid
Presenter(s):
[Wang]
[Deng]
[Kong]
[Prasad]
[Xiong]
[Zhu]
[SIGGRAPH 2021]
Total relighting: learning to relight portraits for background replacement
Presenter(s):
[Pandey]
[Orts-Escolano]
[LeGendre]
[Haene]
[Bouaziz]
[Rhemann]
[Debevec]
[Fanello]
[SIGGRAPH 2021]
Tracing versus freehand for evaluating computer-generated drawings
Presenter(s):
[Wang]
[Qju]
[Feng]
[Rushmeier]
[McMillan]
[Dorsey]
[SIGGRAPH 2021]
Transfer matrix based layered materials rendering
Presenter(s):
[Randrianandrasana]
[Callet]
[Lucas]
[SIGGRAPH 2021]
TransPose: real-time 3D human translation and pose estimation with six inertial sensors
Presenter(s):
[Yi]
[Zhou]
[Xu]
[SIGGRAPH 2021]
TryOnGAN: body-aware try-on via layered interpolation
Presenter(s):
[Lewis]
[Varadharajan]
[Kemelmacher-Shlizerman]
[SIGGRAPH 2021]
Unified particle system for multiple-fluid flow and porous material
Presenter(s):
[Ren]
[Xu]
[Li]
[SIGGRAPH 2021]
Unsupervised learning for cuboid shape abstraction via joint segmentation from point clouds
Presenter(s):
[Yang]
[Chen]
[SIGGRAPH 2021]
Using isometries for computational design and fabrication
Presenter(s):
[Jiang]
[Wang]
[Inza]
[Dellinger]
[Rist]
[Wallner]
[Pottmann]
[SIGGRAPH 2021]
Video recoloring via spatial-temporal geometric palettes
Presenter(s):
[Du]
[Lei]
[Xu]
[Tan]
[Gingold]
[SIGGRAPH 2021]
Volumetric appearance stylization with stylizing kernel prediction network
Presenter(s):
[Guo]
[Li]
[Zong]
[Liu]
[He]
[Guo]
[Yan]
[SIGGRAPH 2021]
Weakly-supervised contrastive learning in path manifold for Monte Carlo image reconstruction
Presenter(s):
[Cho]
[Huo]
[Yoon]
[SIGGRAPH 2021]
Total relighting: learning to relight portraits for background replacement
Presenter(s):
[Pandey]
[Orts-Escolano]
[LeGendre]
[Haene]
[Bouaziz]
[Rhemann]
[Debevec]
[Fanello]
[SIGGRAPH 2021]
Interactive modelling of volumetric musculoskeletal anatomy
Presenter(s):
[Abdrashitov]
[Bang]
[Levin]
[Singh]
[Jacobson]
[SIGGRAPH 2021]
Only a matter of style: age transformation using a style-based regression model
Presenter(s):
[Alaluf]
[Patashnik]
[Cohen-Or]
[SIGGRAPH 2021]
Driving-signal aware full-body avatars
Presenter(s):
[Bagautdinov]
[Wu]
[Simon]
[Prada]
[Shiratori]
[Wei]
[Xu]
[Sheikh]
[Saragih]
[SIGGRAPH 2021]
Systematically differentiating parametric discontinuities
Presenter(s):
[Bangaru]
[Michel]
[Mu]
[Bernstein]
[Li]
[Ragan-Kelley]
[SIGGRAPH 2021]
Geometry and tool motion planning for curvature adapted CNC machining
Presenter(s):
[Barton]
[Bizzarri]
[Rist]
[Sliusarenko]
[Pottmann]
[SIGGRAPH 2021]
An inverse method for the exploration of layered material appearance
Presenter(s):
[Bati]
[Barla]
[Pacanowski]
[SIGGRAPH 2021]
Deep relightable appearance models for animatable faces
Presenter(s):
[Bi]
[Lombardi]
[Saito]
[Simon]
[Wei]
[Mcphail]
[Ramamoorthi]
[Sheikh]
[Saragih]
[SIGGRAPH 2021]
WRAPD: weighted rotation-aware ADMM for parameterization and deformation
Presenter(s):
[Brown]
[Narain]
[SIGGRAPH 2021]
A time-independent deformer for elastic contacts
Presenter(s):
[Brunel]
[Bénard]
[Guennebaud]
[SIGGRAPH 2021]
Displaced signed distance fields for additive manufacturing
Presenter(s):
[Brunton]
[Rmaileh]
[SIGGRAPH 2021]
Low-cost SPAD sensing for non-line-of-sight tracking, material classification and depth imaging
Presenter(s):
[Callenberg]
[Shi]
[Heide]
[Hullin]
[SIGGRAPH 2021]
Real-time 3D neural facial animation from binocular video
Presenter(s):
[Cao]
[Agrawal]
[Torre]
[Chen]
[Saragih]
[Simon]
[Sheikh]
[SIGGRAPH 2021]
A momentum-conserving implicit material point method for surface tension with contact angles and spatial gradients
Presenter(s):
[Chen]
[Kala]
[Marquez-Razon]
[Gueidon]
[Hyde]
[Teran]
[SIGGRAPH 2021]
Bistable auxetic surface structures
Presenter(s):
[Chen]
[Panetta]
[Schnaubelt]
[Pauly]
[SIGGRAPH 2021]
Capturing detailed deformations of moving human bodies
Presenter(s):
[Chen]
[Park]
[Macit]
[Kavan]
[SIGGRAPH 2021]
ChoreoMaster: choreography-oriented music-driven dance synthesis
Presenter(s):
[Chen]
[Tand]
[Lei]
[Zhang]
[Guo]
[Zhang]
[Hu]
[SIGGRAPH 2021]
DeepFaceEditing: deep face generation and editing with disentangled geometry and appearance control
Presenter(s):
[Chen]
[Liu]
[Lai]
[Rosin]
[Li]
[Fu]
[Gao]
[SIGGRAPH 2021]
MoCap-solver: a neural solver for optical motion capture data
Presenter(s):
[Chen]
[Wang]
[Zhang]
[Xu]
[Zhang]
[Hu]
[SIGGRAPH 2021]
Multiscale cholesky preconditioning for ill-conditioned problems
Presenter(s):
[Chen]
[Schäfer]
[Huang]
[Desbrun]
[SIGGRAPH 2021]
Weakly-supervised contrastive learning in path manifold for Monte Carlo image reconstruction
Presenter(s):
[Cho]
[Huo]
[Yoon]
[SIGGRAPH 2021]
Learning meaningful controls for fluids
Presenter(s):
[Chu]
[Thuerey]
[Seidel]
[Theobalt]
[Zayer]
[SIGGRAPH 2021]
Boundary-sampled halfspaces: a new representation for constructive solid modeling
Presenter(s):
[Du]
[Zhou]
[Carr]
[Ju]
[SIGGRAPH 2021]
Video recoloring via spatial-temporal geometric palettes
Presenter(s):
[Du]
[Lei]
[Xu]
[Tan]
[Gingold]
[SIGGRAPH 2021]
Authoring consistent landscapes with flora and fauna
Presenter(s):
[Ecormier-Nocca]
[Cordonnier]
[Carrez]
[Moigne]
[Memari]
[Benes]
[Cani]
[SIGGRAPH 2021]
Guaranteed globally injective 3D deformation processing
Presenter(s):
[Fang]
[Li]
[Jiang]
[Kaufman]
[SIGGRAPH 2021]
Revisiting integration in the material point method: a scheme for easier separation and less dissipation
Presenter(s):
[Fei]
[Wu]
[SIGGRAPH 2021]
Learning an animatable detailed 3D face model from in-the-wild images
Presenter(s):
[Feng]
[Feng]
[Black]
[Bolkart]
[SIGGRAPH 2021]
Intersection-free rigid body dynamics
Presenter(s):
[Ferguson]
[Li]
[Schneider]
[Ureta]
[Langlois]
[Jiang]
[Zorin]
[Kaufman]
[Panozzo]
[SIGGRAPH 2021]
SWAGAN: a style-based wavelet-driven generative model
Presenter(s):
[Gal]
[Hochberg]
[Bermano]
[Cohen-Or]
[SIGGRAPH 2021]
Foldover-free maps in 50 lines of code
Presenter(s):
[Garanzha]
[Kaporin]
[Kudryavtseva]
[Protais]
[Ray]
[Sokolov]
[SIGGRAPH 2021]
Discrete conformal equivalence of polyhedral surfaces
Presenter(s):
[Gillespie]
[Springborn]
[Crane]
[SIGGRAPH 2021]
Neural scene graph rendering
Presenter(s):
[Granskog]
[Schnabel]
[Rousselle]
[Novák]
[SIGGRAPH 2021]
Highlight-aware two-stream network for single-image SVBRDF acquisition
Presenter(s):
[Guo]
[Lai]
[Tao]
[Cai]
[Wang]
[Guo]
[Yan]
[SIGGRAPH 2021]
Volumetric appearance stylization with stylizing kernel prediction network
Presenter(s):
[Guo]
[Li]
[Zong]
[Liu]
[He]
[Guo]
[Yan]
[SIGGRAPH 2021]
Real-time deep dynamic characters
Presenter(s):
[Habermann]
[Liu]
[Xu]
[Zollhoefer]
[Pons-Moll]
[Theobalt]
[SIGGRAPH 2021]
Fire in paradise: mesoscale simulation of wildfires
Presenter(s):
[Hädrich]
[Banuti]
[Palubicki]
[Pirk]
[Michels]
[SIGGRAPH 2021]
Endless loops: detecting and animating periodic patterns in still images
Presenter(s):
[Halperin]
[Hakim]
[Vantzos]
[Hochman]
[Benaim]
[Sassy]
[Kupchik]
[Bibi]
[Fried]
[SIGGRAPH 2021]
QuanTaichi: a compiler for quantized simulations
Presenter(s):
[Hu]
[Liu]
[Yang]
[Xu]
[Kuang]
[Xu]
[Dai]
[Freeman]
[Durand]
[SIGGRAPH 2021]
Designing actuation systems for animatronic figures via globally optimal discrete search
Presenter(s):
[Huber]
[Poranne]
[Coros]
[SIGGRAPH 2021]
Interactive Monte Carlo denoising using affinity of neural features
Presenter(s):
[Işık]
[Mullia]
[Fisher]
[Eisenmann]
[Gharbi]
[SIGGRAPH 2021]
StyleCariGAN: caricature generation via StyleGAN feature map modulation
Presenter(s):
[Jang]
[Ju]
[Jung]
[Yang]
[Tong]
[Lee]
[SIGGRAPH 2021]
SANM: a symbolic asymptotic numerical solver with applications in mesh deformation
Presenter(s):
[Jia]
[SIGGRAPH 2021]
Bijective and coarse high-order tetrahedral meshes
Presenter(s):
[Jiang]
[Zhang]
[Hu]
[Schneider]
[Zorin]
[Panozzo]
[SIGGRAPH 2021]
Using isometries for computational design and fabrication
Presenter(s):
[Jiang]
[Wang]
[Inza]
[Dellinger]
[Rist]
[Wallner]
[Pottmann]
[SIGGRAPH 2021]
ShapeMOD: macro operation discovery for 3D shape programs
Presenter(s):
[Jones]
[Charatan]
[Guerrero]
[Mitra]
[Ritchie]
[SIGGRAPH 2021]
Knit sketching: from cut & sew patterns to machine-knit garments
Presenter(s):
[Kaspar]
[Wu]
[Luo]
[Makatura]
[Matusik]
[SIGGRAPH 2021]
Constrained projective dynamics: real-time simulation of deformable objects with energy-momentum conservation
Presenter(s):
[Kee]
[Um]
[Jeong]
[Han]
[SIGGRAPH 2021]
An unbiased ray-marching transmittance estimator
Presenter(s):
[Kettunen]
[d’Eon]
[Pantaleoni]
[Novák]
[SIGGRAPH 2021]
Dynamic closest color warping to sort and compare palettes
Presenter(s):
[Kim]
[Choi]
[SIGGRAPH 2021]
Optimizing UI layouts for deformable face-rig manipulation
Presenter(s):
[Kim]
[Singh]
[SIGGRAPH 2021]
A perceptual model for eccentricity-dependent spatio-temporal flicker fusion and its applications to foveated graphics
Presenter(s):
[Krajancich]
[Kellnhofer]
[Wetzstein]
[SIGGRAPH 2021]
NeuMIP: multi-resolution neural materials
Presenter(s):
[Kuznetsov]
[Mullia]
[Xu]
[Hasan]
[Ramamoorthi]
[SIGGRAPH 2021]
Medial IPC: accelerated incremental potential contact with medial elastics
Presenter(s):
[Lan]
[Yang]
[Kaufman]
[Yao]
[Li]
[Jiang]
[SIGGRAPH 2021]
Direct delta mush skinning compression with continuous examples
Presenter(s):
[Le]
[Villeneuve]
[Gonzalez-Ochoa]
[SIGGRAPH 2021]
A mathematical foundation for foundation paper pieceable quilts
Presenter(s):
[Leake]
[Bernstein]
[Davis]
[Agrawala]
[SIGGRAPH 2021]
Learning a family of motor skills from a single motion clip
Presenter(s):
[Lee]
[Lee]
[Lee]
[Lee]
[SIGGRAPH 2021]
Learning time-critical responses for interactive character control
Presenter(s):
[Lee]
[Min]
[Lee]
[Lee]
[SIGGRAPH 2021]
TryOnGAN: body-aware try-on via layered interpolation
Presenter(s):
[Lewis]
[Varadharajan]
[Kemelmacher-Shlizerman]
[SIGGRAPH 2021]
SP-GAN: sphere-guided 3D shape generation and manipulation
Presenter(s):
[Li]
[Li]
[Hui]
[Fu]
[SIGGRAPH 2021]
Real-time locally injective volumetric deformation
Organizer(s):
[Liao]
[Chen]
[Hua]
[Liu]
[Weber]
[SIGGRAPH 2021]
Knitting 4D garments with elasticity controlled for body motion
Presenter(s):
[Liu]
[Han]
[Zhang]
[Chen]
[Lai]
[Doubrovski]
[Whiting]
[Wang]
[SIGGRAPH 2021]
Modeling and fabrication with specified discrete equivalence classes
Presenter(s):
[Liu]
[Zhang]
[Zhang]
[Ye]
[Liu]
[Fu]
[SIGGRAPH 2021]
Surface multigrid via intrinsic prolongation
Presenter(s):
[Liu]
[Zhang]
[Ben-Chen]
[Jacobson]
[SIGGRAPH 2021]
Mixture of volumetric primitives for efficient neural rendering
Presenter(s):
[Lombardi]
[Simon]
[Schwartz]
[Zollhoefer]
[Sheikh]
[Saragih]
[SIGGRAPH 2021]
DiffAqua: a differentiable computational design pipeline for soft underwater swimmers with shape interpolation
Presenter(s):
[Ma]
[Du]
[Zhang]
[Wu]
[Spielberg]
[Katzschmann]
[Matusik]
[SIGGRAPH 2021]
Free-form scanning of non-planar appearance with neural trace photography
Presenter(s):
[Ma]
[Kang]
[Zhu]
[Wu]
[Zhou]
[SIGGRAPH 2021]
Pareto gamuts: exploring optimal designs across varying contexts
Presenter(s):
[Makatura]
[Guo]
[Schulz]
[Solomon]
[Matusik]
[SIGGRAPH 2021]
Guaranteed-quality higher-order triangular meshing of 2D domains
Presenter(s):
[Mandad]
[Campen]
[SIGGRAPH 2021]
FovVideoVDP: a visible difference predictor for wide field-of-view video
Presenter(s):
[Mantiuk]
[Denes]
[Chapiro]
[Kaplayan]
[Rufo]
[Bachy]
[Lian]
[Patney]
[SIGGRAPH 2021]
Acorn: adaptive coordinate networks for neural scene representation
Presenter(s):
[Martel]
[Lindell]
[Lin]
[Chan]
[Monteiro]
[Wetzstein]
[SIGGRAPH 2021]
Orienting point clouds with dipole propagation
Presenter(s):
[Metzer]
[Hanocka]
[Zorin]
[Giryes]
[Panozzo]
[Cohen-Or]
[SIGGRAPH 2021]
DAG amendment for inverse control of parametric shapes
Presenter(s):
[Michel]
[Boubekeur]
[SIGGRAPH 2021]
General virtual sketching framework for vector line art
Presenter(s):
[Mo]
[Simo-Serra]
[Gao]
[Zou]
[Wang]
[SIGGRAPH 2021]
Real-time neural radiance caching for path tracing
Presenter(s):
[Müller]
[Rousselle]
[Novák]
[Keller]
[SIGGRAPH 2021]
Kelvin transformations for simulations on infinite domains
Presenter(s):
[Nabizadeh]
[Ramamoorthi]
[Chern]
[SIGGRAPH 2021]
KnitKit: a flexible system for machine knitting of customizable textiles
Presenter(s):
[Nader]
[Quek]
[Chia]
[Weeger]
[Yeung]
[SIGGRAPH 2021]
A gradient-based framework for 3D print appearance optimization
Presenter(s):
[Nindel]
[Iser]
[Rittig]
[Wilkie]
[Křivánek]
[SIGGRAPH 2021]
Computational inverse design of surface-based inflatables
Presenter(s):
[Panetta]
[Isvoranu]
[Chen]
[Siéfert]
[Roman]
[Pauly]
[SIGGRAPH 2021]
Computational design of weingarten surfaces
Presenter(s):
[Pellis]
[Kilian]
[Pottmann]
[Pauly]
[SIGGRAPH 2021]
AMP: adversarial motion priors for stylized physics-based character control
Presenter(s):
[Peng]
[Ma]
[Abbeel]
[Levine]
[Kanazawa]
[SIGGRAPH 2021]
Reliable feature-line driven quad-remeshing
Presenter(s):
[Pietroni]
[Nuvoli]
[Alderighi]
[Cignoni]
[Tarini]
[SIGGRAPH 2021]
PH-CPF: planar hexagonal meshing using coordinate power fields
Presenter(s):
[Pluta]
[Edelstein]
[Vaxman]
[Ben-Chen]
[SIGGRAPH 2021]
Fast linking numbers for topology verification of loopy structures
Presenter(s):
[Qu]
[James]
[SIGGRAPH 2021]
PhotoApp: photorealistic appearance editing of head portraits
Presenter(s):
[R.]
[Tewari]
[Dib]
[Weyrich]
[Bickel]
[Seidel]
[Pfister]
[Matusik]
[Elgharib]
[Theobalt]
[SIGGRAPH 2021]
Transfer matrix based layered materials rendering
Presenter(s):
[Randrianandrasana]
[Callet]
[Lucas]
[SIGGRAPH 2021]
3D weaving with curved ribbons
Presenter(s):
[Ren]
[Panetta]
[Chen]
[Isvoranu]
[Poincloux]
[Brandt]
[Martin]
[Pauly]
[SIGGRAPH 2021]
Unified particle system for multiple-fluid flow and porous material
Presenter(s):
[Ren]
[Xu]
[Li]
[SIGGRAPH 2021]
Learning contact corrections for handle-based subspace dynamics
Presenter(s):
[Romero]
[Casas]
[Rodríguez]
[Otaduy]
[SIGGRAPH 2021]
Physical validation of simulators in computer graphics: a new framework dedicated to slender elastic structures and frictional contact
Presenter(s):
[Romero]
[Ly]
[Rasheed]
[Charrondière]
[Lazarus]
[Neukirch]
[Bertails-Descoubes]
[SIGGRAPH 2021]
Solid-fluid interaction with surface-tension-dominant contact
Presenter(s):
[Ruan]
[Liu]
[Zhu]
[Sueda]
[Wang]
[Chen]
[SIGGRAPH 2021]
Fast diffraction pathfinding for dynamic sound propagation
Presenter(s):
[Schissler]
[Mückl]
[Calamia]
[SIGGRAPH 2021]
Swept volumes via spacetime numerical continuation
Presenter(s):
[Sellán]
[Aigerman]
[Jacobson]
[SIGGRAPH 2021]
The effect of shape and illumination on material perception: model and applications
Presenter(s):
[Serrano]
[Chen]
[Wang]
[Piovarči]
[Seidel]
[Didyk]
[Myszkowski]
[SIGGRAPH 2021]
High-order differentiable autoencoder for nonlinear model reduction
Presenter(s):
[Shen]
[Yang]
[Shao]
[Wang]
[Jiang]
[Lan]
[Zhou]
[SIGGRAPH 2021]
Neural monocular 3D human motion capture with physical awareness
Presenter(s):
[Shimada]
[Golyanik]
[Xu]
[Perez]
[Theobalt]
[SIGGRAPH 2021]
HodgeNet: learning spectral geometry on triangle meshes
Presenter(s):
[Smirnov]
[Solomon]
[SIGGRAPH 2021]
Constrained willmore surfaces
Presenter(s):
[Soliman]
[Chern]
[Diamanti]
[Knöppel]
[Pinkall]
[Schröder]
[SIGGRAPH 2021]
AgileGAN: stylizing portraits by inversion-consistent transfer learning
Presenter(s):
[Song]
[Luo]
[Liu]
[Ma]
[Lai]
[Zheng]
[Cham]
[SIGGRAPH 2021]
Mechanics-aware deformation of yarn pattern geometry
Presenter(s):
[Sperl]
[Narain]
[Wojtan]
[SIGGRAPH 2021]
Learning active quasistatic physics-based models from data
Presenter(s):
[Srinivasan]
[Wang]
[Rojas]
[Klár]
[Kavan]
[Sifakis]
[SIGGRAPH 2021]
Neural animation layering for synthesizing martial arts movements
Presenter(s):
[Starke]
[Zhao]
[Zinno]
[Komura]
[SIGGRAPH 2021]
A unified second-order accurate in time MPM formulation for simulating viscoelastic liquids with phase change
Presenter(s):
[Su]
[Xue]
[Han]
[Jiang]
[Aanjaneya]
[SIGGRAPH 2021]
End-to-end complex lens design with differentiate ray tracing
Presenter(s):
[Sun]
[Wang]
[Fu]
[Dun]
[Heidrich]
[SIGGRAPH 2021]
Designing an encoder for StyleGAN image manipulation
Presenter(s):
[Tov]
[Alaluf]
[Nitzan]
[Patashnik]
[Cohen-Or]
[SIGGRAPH 2021]
The shape matching element method: direct animation of curved surface models
Presenter(s):
[Trusty]
[Chen]
[Levin]
[SIGGRAPH 2021]
StrokeStrip: joint parameterization and fitting of stroke clusters
Presenter(s):
[Van Mossel]
[Liu]
[Vining]
[Bessmeltsev]
[Sheffer]
[SIGGRAPH 2021]
A non-exponential transmittance model for volumetric scene representations
Presenter(s):
[Vicini]
[Jakob]
[Kaplayan]
[SIGGRAPH 2021]
Path replay backpropagation: differentiating light paths using constant memory and linear time
Presenter(s):
[Vicini]
[Speierer]
[Jakob]
[SIGGRAPH 2021]
Beyond blur: real-time ventral metamers for foveated rendering
Presenter(s):
[Walton]
[Dos Anjos]
[Friston]
[Swapp]
[Akşit]
[Steed]
[Ritschel]
[SIGGRAPH 2021]
Fast quasi-harmonic weights for geometric data interpolation
Presenter(s):
[Wang]
[Solomon]
[SIGGRAPH 2021]
MOCCA: modeling and optimizing cone-joints for complex assemblies
Presenter(s):
[Wang]
[Song]
[Pauly]
[SIGGRAPH 2021]
Thin-film smoothed particle hydrodynamics fluid
Presenter(s):
[Wang]
[Deng]
[Kong]
[Prasad]
[Xiong]
[Zhu]
[SIGGRAPH 2021]
Tracing versus freehand for evaluating computer-generated drawings
Presenter(s):
[Wang]
[Qju]
[Feng]
[Rushmeier]
[McMillan]
[Dorsey]
[SIGGRAPH 2021]
A fitted radiance and attenuation model for realistic atmospheres
Presenter(s):
[Wilkie]
[Vévoda]
[Bashford-Rogers]
[Hosek]
[Iser]
[Kolářová]
[Rittig]
[Křivánek]
[SIGGRAPH 2021]
Fusion 360 gallery: a dataset and environment for programmatic CAD construction from human design sequences
Presenter(s):
[Willis]
[Pu]
[Luo]
[Chu]
[Du]
[Lambourne]
[Solar-Lezama]
[Matusik]
[SIGGRAPH 2021]
Control strategies for physically simulated characters performing two-player competitive sports
Presenter(s):
[Won]
[Gopinath]
[Hodgins]
[SIGGRAPH 2021]
Coarse-to-fine: facial structure editing of portrait images via latent space classifications
Presenter(s):
[Wu]
[Yang]
[Xiao]
[Jin]
[SIGGRAPH 2021]
Eliminating topological errors in neural network rotation estimation using self-selecting ensembles
Presenter(s):
[Xiang]
[SIGGRAPH 2021]
Seamless manga inpainting with semantics awareness
Presenter(s):
[Xie]
[Xia]
[Li]
[Wong]
[SIGGRAPH 2021]
Incompressible flow simulation on vortex segment clouds
Presenter(s):
[Xiong]
[Tao]
[Zhang]
[Feng]
[Zhu]
[SIGGRAPH 2021]
Scalable image-based indoor scene rendering with reflections
Presenter(s):
[Xu]
[Wu]
[Zu]
[Huang]
[Yang]
[Bao]
[Xu]
[SIGGRAPH 2021]
DeepFormableTag: end-to-end generation and recognition of deformable fiducial markers
Presenter(s):
[Yaldiz]
[Meuleman]
[Jang]
[Ha]
[Kim]
[SIGGRAPH 2021]
Unsupervised learning for cuboid shape abstraction via joint segmentation from point clouds
Presenter(s):
[Yang]
[Chen]
[SIGGRAPH 2021]
WireRoom: model-guided explorative design of abstract wire art
Presenter(s):
[Yang]
[Xu]
[Fu]
[Huang]
[SIGGRAPH 2021]
TransPose: real-time 3D human translation and pose estimation with six inertial sensors
Presenter(s):
[Yi]
[Zhou]
[Xu]
[SIGGRAPH 2021]
Discovering diverse athletic jumping strategies
Presenter(s):
[Yin]
[Yang]
[Panne]
[Yin]
[SIGGRAPH 2021]
Monte Carlo estimators for differential light transport
Presenter(s):
[Zeltner]
[Speierer]
[Georgiev]
[Jakob]
[SIGGRAPH 2021]
Antithetic sampling for Monte Carlo differentiable rendering
Presenter(s):
[Zhang]
[Dong]
[Doggett]
[Zhao]
[SIGGRAPH 2021]
Consistent depth of moving objects in video
Presenter(s):
[Zhang]
[Cole]
[Tucker]
[Freeman]
[Dekel]
[SIGGRAPH 2021]
Editable free-viewpoint video using a layered neural representation
Presenter(s):
[Zhang]
[Liu]
[Ye]
[Zhao]
[Zhang]
[Wu]
[Zhang]
[Yu]
[Xu]
[SIGGRAPH 2021]
Learning skeletal articulations with neural blend shapes
Presenter(s):
[Zhang]
[Aberman]
[Hanocka]
[Liu]
[Sorkine-Hornung]
[Chen]
[SIGGRAPH 2021]
ManipNet: neural manipulation synthesis with a hand-object spatial representation
Presenter(s):
[Zhang]
[Ye]
[Shiratori]
[Komura]
[SIGGRAPH 2021]
Path-space differentiable rendering of participating media
Presenter(s):
[Zhang]
[Yu]
[Zhao]
[SIGGRAPH 2021]
ROSEFusion: random optimization for online dense reconstruction under fast camera motion
Presenter(s):
[Zhang]
[Zhu]
[Zheng]
[Xu]
[SIGGRAPH 2021]
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Title
Presenter
![3D weaving with curved ribbons](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Ren_3D-Weaving-with-Curved-Ribbons-150x150.jpg)
3D weaving with curved ribbons Presenter(s): [Ren] [Panetta] [Chen] [Isvoranu] [Poincloux] [Brandt] [Martin] [Pauly]
[SIGGRAPH 2021]
![A fitted radiance and attenuation model for realistic atmospheres](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Wilkie_A-Fitted-Radiance-and-Attenuation-Model-for-Realistic-Atmospheres-150x150.jpg)
A fitted radiance and attenuation model for realistic atmospheres Presenter(s): [Wilkie] [Vévoda] [Bashford-Rogers] [Hosek] [Iser] [Kolářová] [Rittig] [Křivánek]
[SIGGRAPH 2021]
![A gradient-based framework for 3D print appearance optimization](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Nindel_A-Gradient-Based-Framework-for-3D-Print-Appearance-Optimization-150x150.jpg)
A gradient-based framework for 3D print appearance optimization Presenter(s): [Nindel] [Iser] [Rittig] [Wilkie] [Křivánek]
[SIGGRAPH 2021]
![A mathematical foundation for foundation paper pieceable quilts](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Leake_A-Mathematical-Foundation-for-Foundation-Paper-Pieceable-Quilts-150x150.jpg)
A mathematical foundation for foundation paper pieceable quilts Presenter(s): [Leake] [Bernstein] [Davis] [Agrawala]
[SIGGRAPH 2021]
![A momentum-conserving implicit material point method for surface tension with contact angles and spatial gradients](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Chen_A-Momentum-Conserving-Implicit-Material-Point-Method-for-Surface-Tension-with-Contact-Angles-and-Spatial-Gradients-150x150.jpg)
A momentum-conserving implicit material point method for surface tension with contact angles and spatial gradients Presenter(s): [Chen] [Kala] [Marquez-Razon] [Gueidon] [Hyde] [Teran]
[SIGGRAPH 2021]
![A non-exponential transmittance model for volumetric scene representations](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Vicini_A-Non-Exponential-Transmittance-Model-for-Volumetric-Scene-Representations-150x150.jpg)
A non-exponential transmittance model for volumetric scene representations Presenter(s): [Vicini] [Jakob] [Kaplayan]
[SIGGRAPH 2021]
![A perceptual model for eccentricity-dependent spatio-temporal flicker fusion and its applications to foveated graphics](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Krjancich_A-Perceptual-Model-for-Eccentricity-dependent-Spatio-temporal-Flicker-Fusion-and-its-Applications-to-Foveated-Graphics-150x150.jpg)
A perceptual model for eccentricity-dependent spatio-temporal flicker fusion and its applications to foveated graphics Presenter(s): [Krajancich] [Kellnhofer] [Wetzstein]
[SIGGRAPH 2021]
![A time-independent deformer for elastic contacts](https://history.siggraph.org/wp-content/uploads/2022/05/SIGGRAPH2021_Image-Not-Available-150x150.jpg)
A time-independent deformer for elastic contacts Presenter(s): [Brunel] [Bénard] [Guennebaud]
[SIGGRAPH 2021]
![A unified second-order accurate in time MPM formulation for simulating viscoelastic liquids with phase change](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Su_A-Unified-Second-Order-Accurate-in-Time-MPM-Formulation-for-Simulating-Viscoelastic-Liquids-with-Phase-Change-150x150.jpg)
A unified second-order accurate in time MPM formulation for simulating viscoelastic liquids with phase change Presenter(s): [Su] [Xue] [Han] [Jiang] [Aanjaneya]
[SIGGRAPH 2021]
![Acorn: adaptive coordinate networks for neural scene representation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Martel_acorn-Adaptive-Coordinate-Networks-for-Neural-Scene-Representation-150x150.jpg)
Acorn: adaptive coordinate networks for neural scene representation Presenter(s): [Martel] [Lindell] [Lin] [Chan] [Monteiro] [Wetzstein]
[SIGGRAPH 2021]
![AgileGAN: stylizing portraits by inversion-consistent transfer learning](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Song_AgileGAN_-Stylizing-Portraits-by-Inversion-Consistent-Transfer-Learning-150x150.jpg)
AgileGAN: stylizing portraits by inversion-consistent transfer learning Presenter(s): [Song] [Luo] [Liu] [Ma] [Lai] [Zheng] [Cham]
[SIGGRAPH 2021]
![AMP: adversarial motion priors for stylized physics-based character control](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Peng_AMP-Adversarial-Motion-Priors-for-Stylized-Physics-Based-Character-Control-150x150.jpg)
AMP: adversarial motion priors for stylized physics-based character control Presenter(s): [Peng] [Ma] [Abbeel] [Levine] [Kanazawa]
[SIGGRAPH 2021]
![An inverse method for the exploration of layered material appearance](https://history.siggraph.org/wp-content/uploads/2022/05/SIGGRAPH2021_Image-Not-Available-150x150.jpg)
An inverse method for the exploration of layered material appearance Presenter(s): [Bati] [Barla] [Pacanowski]
[SIGGRAPH 2021]
![An unbiased ray-marching transmittance estimator](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Kettunen_An-unbiased-ray-marching-transmittance-estimator-150x150.jpg)
An unbiased ray-marching transmittance estimator Presenter(s): [Kettunen] [d’Eon] [Pantaleoni] [Novák]
[SIGGRAPH 2021]
![Antithetic sampling for Monte Carlo differentiable rendering](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Zhang_Antithetic-Sampling-for-Monte-Carlo-Differentiable-Rendering-150x150.jpg)
Antithetic sampling for Monte Carlo differentiable rendering Presenter(s): [Zhang] [Dong] [Doggett] [Zhao]
[SIGGRAPH 2021]
![Authoring consistent landscapes with flora and fauna](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Carrez_Authoring-Consistent-Landscapes-with-Flora-and-Fauna-150x150.jpg)
Authoring consistent landscapes with flora and fauna Presenter(s): [Ecormier-Nocca] [Cordonnier] [Carrez] [Moigne] [Memari] [Benes] [Cani]
[SIGGRAPH 2021]
![Beyond blur: real-time ventral metamers for foveated rendering](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Walton_Beyond-Blur_-Real-time-Ventral-Metamers-for-Foveated-Rendering-150x150.jpg)
Beyond blur: real-time ventral metamers for foveated rendering Presenter(s): [Walton] [Dos Anjos] [Friston] [Swapp] [Akşit] [Steed] [Ritschel]
[SIGGRAPH 2021]
![Bijective and coarse high-order tetrahedral meshes](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Jiang_Bijective-and-Coarse-High-Order-Tetrahedral-Meshes-150x150.jpg)
Bijective and coarse high-order tetrahedral meshes Presenter(s): [Jiang] [Zhang] [Hu] [Schneider] [Zorin] [Panozzo]
[SIGGRAPH 2021]
![Bistable auxetic surface structures](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Chen_Bistable-Auxetic-Surface-Structures-150x150.jpg)
Bistable auxetic surface structures Presenter(s): [Chen] [Panetta] [Schnaubelt] [Pauly]
[SIGGRAPH 2021]
![Boundary-sampled halfspaces: a new representation for constructive solid modeling](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Du_Boundary-Sampled-Halfspaces-A-New-Representation-for-Constructive-Solid-Modeling-150x150.jpg)
Boundary-sampled halfspaces: a new representation for constructive solid modeling Presenter(s): [Du] [Zhou] [Carr] [Ju]
[SIGGRAPH 2021]
![Capturing detailed deformations of moving human bodies](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Chen_Capturing-Detailed-Deformations-of-Moving-Human-Bodies-150x150.jpg)
Capturing detailed deformations of moving human bodies Presenter(s): [Chen] [Park] [Macit] [Kavan]
[SIGGRAPH 2021]
![ChoreoMaster: choreography-oriented music-driven dance synthesis](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Chen_ChoreoMaster_-Choreography-Oriented-Music-Driven-Dance-Synthesis-150x150.jpg)
ChoreoMaster: choreography-oriented music-driven dance synthesis Presenter(s): [Chen] [Tand] [Lei] [Zhang] [Guo] [Zhang] [Hu]
[SIGGRAPH 2021]
![Coarse-to-fine: facial structure editing of portrait images via latent space classifications](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Wu_Coarse-to-Fine-Facial-Structure-Editing-of-Portrait-Images-via-Latent-Space-Classifications-150x150.jpg)
Coarse-to-fine: facial structure editing of portrait images via latent space classifications Presenter(s): [Wu] [Yang] [Xiao] [Jin]
[SIGGRAPH 2021]
![Computational design of weingarten surfaces](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Pellis_Computational-Design-of-Weingarten-Surfaces-150x150.jpg)
Computational design of weingarten surfaces Presenter(s): [Pellis] [Kilian] [Pottmann] [Pauly]
[SIGGRAPH 2021]
![Computational inverse design of surface-based inflatables](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Panetta_Computational-Inverse-Design-of-Surface-based-Inflatables-150x150.jpg)
Computational inverse design of surface-based inflatables Presenter(s): [Panetta] [Isvoranu] [Chen] [Siéfert] [Roman] [Pauly]
[SIGGRAPH 2021]
![Consistent depth of moving objects in video](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Zhang_Consistent-Depth-of-Moving-Objects-in-Video-150x150.jpg)
Consistent depth of moving objects in video Presenter(s): [Zhang] [Cole] [Tucker] [Freeman] [Dekel]
[SIGGRAPH 2021]
![Constrained projective dynamics: real-time simulation of deformable objects with energy-momentum conservation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Kee_Constrained-Projective-Dynamics_-Real-Time-Simulation-of-Deformable-Objects-with-Energy-Momentum-Conservation-150x150.jpg)
Constrained projective dynamics: real-time simulation of deformable objects with energy-momentum conservation Presenter(s): [Kee] [Um] [Jeong] [Han]
[SIGGRAPH 2021]
![Constrained willmore surfaces](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Soliman_Constrained-Willmore-Surfaces-150x150.jpg)
Constrained willmore surfaces Presenter(s): [Soliman] [Chern] [Diamanti] [Knöppel] [Pinkall] [Schröder]
[SIGGRAPH 2021]
![Control strategies for physically simulated characters performing two-player competitive sports](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Won_Control-Strategies-for-Physically-Simulated-Characters-Performing-Two-player-Competitive-Sports-150x150.jpg)
Control strategies for physically simulated characters performing two-player competitive sports Presenter(s): [Won] [Gopinath] [Hodgins]
[SIGGRAPH 2021]
![DAG amendment for inverse control of parametric shapes](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Michel_DAG-Amendment-for-Inverse-Control-of-Parametric-Shapes-150x150.jpg)
DAG amendment for inverse control of parametric shapes Presenter(s): [Michel] [Boubekeur]
[SIGGRAPH 2021]
![Deep relightable appearance models for animatable faces](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Bi_Deep-Relightable-Appearance-Models-for-Animatable-Faces-150x150.jpg)
Deep relightable appearance models for animatable faces Presenter(s): [Bi] [Lombardi] [Saito] [Simon] [Wei] [Mcphail] [Ramamoorthi] [Sheikh] [Saragih]
[SIGGRAPH 2021]
![DeepFaceEditing: deep face generation and editing with disentangled geometry and appearance control](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Chen_DeepFaceEditing-Deep-Face-Generation-and-Editing-with-Disentangled-Geometry-and-Appearance-Control-150x150.jpg)
DeepFaceEditing: deep face generation and editing with disentangled geometry and appearance control Presenter(s): [Chen] [Liu] [Lai] [Rosin] [Li] [Fu] [Gao]
[SIGGRAPH 2021]
![DeepFormableTag: end-to-end generation and recognition of deformable fiducial markers](https://history.siggraph.org/wp-content/uploads/2022/05/SIGGRAPH2021_Image-Not-Available-150x150.jpg)
DeepFormableTag: end-to-end generation and recognition of deformable fiducial markers Presenter(s): [Yaldiz] [Meuleman] [Jang] [Ha] [Kim]
[SIGGRAPH 2021]
![Designing actuation systems for animatronic figures via globally optimal discrete search](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Huber_Designing-actuation-systems-for-animatronic-figures-via-globally-optimal-discrete-search-150x150.jpg)
Designing actuation systems for animatronic figures via globally optimal discrete search Presenter(s): [Huber] [Poranne] [Coros]
[SIGGRAPH 2021]
![Designing an encoder for StyleGAN image manipulation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Tov_Designing-an-Encoder-for-StyleGAN-Image-Manipulation-150x150.jpg)
Designing an encoder for StyleGAN image manipulation Presenter(s): [Tov] [Alaluf] [Nitzan] [Patashnik] [Cohen-Or]
[SIGGRAPH 2021]
![DiffAqua: a differentiable computational design pipeline for soft underwater swimmers with shape interpolation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Ma_DiffAqua-A-Differentiable-Computational-Design-Pipeline-for-Soft-Underwater-Swimmers-with-Shape-Interpolation-150x150.jpg)
DiffAqua: a differentiable computational design pipeline for soft underwater swimmers with shape interpolation Presenter(s): [Ma] [Du] [Zhang] [Wu] [Spielberg] [Katzschmann] [Matusik]
[SIGGRAPH 2021]
![Direct delta mush skinning compression with continuous examples](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Le_Direct-Delta-Mush-Skinning-Compression-with-Continuous-Examples-150x150.jpg)
Direct delta mush skinning compression with continuous examples Presenter(s): [Le] [Villeneuve] [Gonzalez-Ochoa]
[SIGGRAPH 2021]
![Discovering diverse athletic jumping strategies](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Yin_Discovering-Diverse-Athletic-Jumping-Strategies-150x150.jpg)
Discovering diverse athletic jumping strategies Presenter(s): [Yin] [Yang] [Panne] [Yin]
[SIGGRAPH 2021]
![Discrete conformal equivalence of polyhedral surfaces](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Gillespie_Discrete-Conformal-Equivalence-of-Polyhedral-Surfaces-150x150.jpg)
Discrete conformal equivalence of polyhedral surfaces Presenter(s): [Gillespie] [Springborn] [Crane]
[SIGGRAPH 2021]
![Displaced signed distance fields for additive manufacturing](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Brunton_Displaced-Signed-Distance-Fields-for-Additive-Manufacturing-150x150.jpg)
Displaced signed distance fields for additive manufacturing Presenter(s): [Brunton] [Rmaileh]
[SIGGRAPH 2021]
![Driving-signal aware full-body avatars](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Wu_Driving-Signal-Aware-Full-Body-Avatars-150x150.jpg)
Driving-signal aware full-body avatars Presenter(s): [Bagautdinov] [Wu] [Simon] [Prada] [Shiratori] [Wei] [Xu] [Sheikh] [Saragih]
[SIGGRAPH 2021]
![Dynamic closest color warping to sort and compare palettes](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Kim_Dynamic-Closest-Color-Warping-to-Sort-and-Compare-Palettes-150x150.jpg)
Dynamic closest color warping to sort and compare palettes Presenter(s): [Kim] [Choi]
[SIGGRAPH 2021]
![Editable free-viewpoint video using a layered neural representation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Zhang_Editable-Free-Viewpoint-Video-using-a-Layered-Neural-Representation-150x150.jpg)
Editable free-viewpoint video using a layered neural representation Presenter(s): [Zhang] [Liu] [Ye] [Zhao] [Zhang] [Wu] [Zhang] [Yu] [Xu]
[SIGGRAPH 2021]
![Eliminating topological errors in neural network rotation estimation using self-selecting ensembles](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Xiang_Eliminating-Topological-Errors-in-Neural-Network-Rotation-Estimation-Using-Self-selecting-Ensembles-150x150.jpg)
Eliminating topological errors in neural network rotation estimation using self-selecting ensembles Presenter(s): [Xiang]
[SIGGRAPH 2021]
![End-to-end complex lens design with differentiate ray tracing](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Sun_End-to-End-Complex-Lens-Design-with-Differentiable-Ray-Tracing-150x150.jpg)
End-to-end complex lens design with differentiate ray tracing Presenter(s): [Sun] [Wang] [Fu] [Dun] [Heidrich]
[SIGGRAPH 2021]
![Endless loops: detecting and animating periodic patterns in still images](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Halperin_Endless-Loops-Detecting-and-Animating-Periodic-Patterns-in-Still-Images-150x150.jpg)
Endless loops: detecting and animating periodic patterns in still images Presenter(s): [Halperin] [Hakim] [Vantzos] [Hochman] [Benaim] [Sassy] [Kupchik] [Bibi] [Fried]
[SIGGRAPH 2021]
![Fast diffraction pathfinding for dynamic sound propagation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Schissler_Fast-Diffraction-Pathfinding-for-Dynamic-Sound-Propagation-150x150.jpg)
Fast diffraction pathfinding for dynamic sound propagation Presenter(s): [Schissler] [Mückl] [Calamia]
[SIGGRAPH 2021]
![Fast linking numbers for topology verification of loopy structures](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-James_Fast-Linking-Numbers-for-Topology-Verification-of-Loopy-Structures-150x150.jpg)
Fast linking numbers for topology verification of loopy structures Presenter(s): [Qu] [James]
[SIGGRAPH 2021]
![Fast quasi-harmonic weights for geometric data interpolation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Wang_Fast-Quasi-Harmonic-Weights-for-Geometric-Data-Interpolation-150x150.jpg)
Fast quasi-harmonic weights for geometric data interpolation Presenter(s): [Wang] [Solomon]
[SIGGRAPH 2021]
![Fire in paradise: mesoscale simulation of wildfires](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Hadrich_Fire-in-Paradise1-Mesoscale-Simulation-of-Wildfires-150x150.jpg)
Fire in paradise: mesoscale simulation of wildfires Presenter(s): [Hädrich] [Banuti] [Palubicki] [Pirk] [Michels]
[SIGGRAPH 2021]
![Foldover-free maps in 50 lines of code](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Garanzha_Foldover-free-maps-in-50-lines-of-code-150x150.jpg)
Foldover-free maps in 50 lines of code Presenter(s): [Garanzha] [Kaporin] [Kudryavtseva] [Protais] [Ray] [Sokolov]
[SIGGRAPH 2021]
![FovVideoVDP: a visible difference predictor for wide field-of-view video](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Mantiuk_FovVideoVDP-A-visible-difference-predictor-for-wide-field-of-view-video-150x150.jpg)
FovVideoVDP: a visible difference predictor for wide field-of-view video Presenter(s): [Mantiuk] [Denes] [Chapiro] [Kaplayan] [Rufo] [Bachy] [Lian] [Patney]
[SIGGRAPH 2021]
![Free-form scanning of non-planar appearance with neural trace photography](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Ma_Free-form-Scanning-of-Non-planar-Appearance-with-Neural-Trace-Photography-150x150.jpg)
Free-form scanning of non-planar appearance with neural trace photography Presenter(s): [Ma] [Kang] [Zhu] [Wu] [Zhou]
[SIGGRAPH 2021]
![Fusion 360 gallery: a dataset and environment for programmatic CAD construction from human design sequences](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Willis_Fusion-360-Gallery_-A-Dataset-and-Environment-for-Programmatic-CAD-Construction-from-Human-Design-Sequences-150x150.jpg)
Fusion 360 gallery: a dataset and environment for programmatic CAD construction from human design sequences Presenter(s): [Willis] [Pu] [Luo] [Chu] [Du] [Lambourne] [Solar-Lezama] [Matusik]
[SIGGRAPH 2021]
![General virtual sketching framework for vector line art](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Mo_General-Virtual-Sketching-Framework-for-Vector-Line-Art-150x150.jpg)
General virtual sketching framework for vector line art Presenter(s): [Mo] [Simo-Serra] [Gao] [Zou] [Wang]
[SIGGRAPH 2021]
![Geometry and tool motion planning for curvature adapted CNC machining](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Barton_Geometry-and-tool-motion-planning-for-curvature-adapted-CNC-machining-150x150.jpg)
Geometry and tool motion planning for curvature adapted CNC machining Presenter(s): [Barton] [Bizzarri] [Rist] [Sliusarenko] [Pottmann]
[SIGGRAPH 2021]
![Guaranteed globally injective 3D deformation processing](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Fang_Guaranteed-Globally-Injective-3D-Deformation-Processing-150x150.jpg)
Guaranteed globally injective 3D deformation processing Presenter(s): [Fang] [Li] [Jiang] [Kaufman]
[SIGGRAPH 2021]
![Guaranteed-quality higher-order triangular meshing of 2D domains](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Mandad_Guaranteed-Quality-Higher-Order-Triangular-Meshing-of-2D-Domains-150x150.jpg)
Guaranteed-quality higher-order triangular meshing of 2D domains Presenter(s): [Mandad] [Campen]
[SIGGRAPH 2021]
![Hierarchical neural reconstruction for path guiding using hybrid path and photon samples](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Zhu_Hierarchical-Neural-Reconstruction-for-Path-Guiding-Using-Hybrid-Path-and-Photon-Samples-150x150.jpg)
Hierarchical neural reconstruction for path guiding using hybrid path and photon samples Presenter(s): [Zhu] [Xu] [Sun] [Kuznetsov] [Meyer] [Jensen] [Su] [Ramamoorthi]
[SIGGRAPH 2021]
![High-order differentiable autoencoder for nonlinear model reduction](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Shen_High-order-Differentiable-Autoencoder-for-Nonlinear-Model-Reduction-150x150.jpg)
High-order differentiable autoencoder for nonlinear model reduction Presenter(s): [Shen] [Yang] [Shao] [Wang] [Jiang] [Lan] [Zhou]
[SIGGRAPH 2021]
![Highlight-aware two-stream network for single-image SVBRDF acquisition](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Guo_Highlight-Aware-Two-Stream-Network-for-Single-Image-SVBRDF-Acquisition-150x150.jpg)
Highlight-aware two-stream network for single-image SVBRDF acquisition Presenter(s): [Guo] [Lai] [Tao] [Cai] [Wang] [Guo] [Yan]
[SIGGRAPH 2021]
![HodgeNet: learning spectral geometry on triangle meshes](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Smirnov_HodgeNet_-Learning-Spectral-Geometry-on-Triangle-Meshes-150x150.jpg)
HodgeNet: learning spectral geometry on triangle meshes Presenter(s): [Smirnov] [Solomon]
[SIGGRAPH 2021]
![Incompressible flow simulation on vortex segment clouds](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Xiong_Incompressible-Flow-Simulation-on-Vortex-Segment-Clouds-150x150.jpg)
Incompressible flow simulation on vortex segment clouds Presenter(s): [Xiong] [Tao] [Zhang] [Feng] [Zhu]
[SIGGRAPH 2021]
![Interactive modelling of volumetric musculoskeletal anatomy](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Bang_Interactive-Modelling-of-Volumetric-Musculoskeletal-Anatomy-150x150.jpg)
Interactive modelling of volumetric musculoskeletal anatomy Presenter(s): [Abdrashitov] [Bang] [Levin] [Singh] [Jacobson]
[SIGGRAPH 2021]
![Interactive Monte Carlo denoising using affinity of neural features](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Isik_Interactive-Monte-Carlo-Denoising-using-Affinity-of-Neural-Features-150x150.jpg)
Interactive Monte Carlo denoising using affinity of neural features Presenter(s): [Işık] [Mullia] [Fisher] [Eisenmann] [Gharbi]
[SIGGRAPH 2021]
![Intersection-free rigid body dynamics](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Ferguson_Intersection-free-Rigid-Body-Dynamics-150x150.jpg)
Intersection-free rigid body dynamics Presenter(s): [Ferguson] [Li] [Schneider] [Ureta] [Langlois] [Jiang] [Zorin] [Kaufman] [Panozzo]
[SIGGRAPH 2021]
![Kelvin transformations for simulations on infinite domains](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Nabizadeh_Kelvin-Transformations-for-Simulations-on-Infinite-Domains-150x150.jpg)
Kelvin transformations for simulations on infinite domains Presenter(s): [Nabizadeh] [Ramamoorthi] [Chern]
[SIGGRAPH 2021]
![Knit sketching: from cut & sew patterns to machine-knit garments](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Kaspar_Knit-Sketching-from-Cut-_-Sew-Patterns-to-Machine-Knit-Garments-150x150.jpg)
Knit sketching: from cut & sew patterns to machine-knit garments Presenter(s): [Kaspar] [Wu] [Luo] [Makatura] [Matusik]
[SIGGRAPH 2021]
![KnitKit: a flexible system for machine knitting of customizable textiles](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Nadar_KnitKit-A-flexible-system-for-machine-knitting-of-customizable-textiles-150x150.jpg)
KnitKit: a flexible system for machine knitting of customizable textiles Presenter(s): [Nader] [Quek] [Chia] [Weeger] [Yeung]
[SIGGRAPH 2021]
![Knitting 4D garments with elasticity controlled for body motion](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Liu_Knitting-4D-Garments-with-Elasticity-Controlled-for-Body-Motion-150x150.jpg)
Knitting 4D garments with elasticity controlled for body motion Presenter(s): [Liu] [Han] [Zhang] [Chen] [Lai] [Doubrovski] [Whiting] [Wang]
[SIGGRAPH 2021]
![Learning a family of motor skills from a single motion clip](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Lee_Learning-a-family-of-motor-skills-from-a-single-motion-clip-150x150.jpg)
Learning a family of motor skills from a single motion clip Presenter(s): [Lee] [Lee] [Lee] [Lee]
[SIGGRAPH 2021]
![Learning active quasistatic physics-based models from data](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Grama_Learning-active-quasistatic-physics-based-models-from-data-150x150.jpg)
Learning active quasistatic physics-based models from data Presenter(s): [Srinivasan] [Wang] [Rojas] [Klár] [Kavan] [Sifakis]
[SIGGRAPH 2021]
![Learning an animatable detailed 3D face model from in-the-wild images](https://history.siggraph.org/wp-content/uploads/2022/05/SIGGRAPH2021_Image-Not-Available-150x150.jpg)
Learning an animatable detailed 3D face model from in-the-wild images Presenter(s): [Feng] [Feng] [Black] [Bolkart]
[SIGGRAPH 2021]
![Learning contact corrections for handle-based subspace dynamics](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Romero_Learning-Contact-Corrections-for-Handle-Based-Subspace-Dynamics-150x150.jpg)
Learning contact corrections for handle-based subspace dynamics Presenter(s): [Romero] [Casas] [Rodríguez] [Otaduy]
[SIGGRAPH 2021]
![Learning meaningful controls for fluids](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Chu_Learning-Meaningful-Controls-for-Fluids-150x150.jpg)
Learning meaningful controls for fluids Presenter(s): [Chu] [Thuerey] [Seidel] [Theobalt] [Zayer]
[SIGGRAPH 2021]
![Learning skeletal articulations with neural blend shapes](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Li_Learning-Skeletal-Articulations-with-Neural-Blend-Shapes-150x150.jpg)
Learning skeletal articulations with neural blend shapes Presenter(s): [Zhang] [Aberman] [Hanocka] [Liu] [Sorkine-Hornung] [Chen]
[SIGGRAPH 2021]
![Learning time-critical responses for interactive character control](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Lee_Learning-Time-Critical-Responses-for-Interactive-Character-Control-150x150.jpg)
Learning time-critical responses for interactive character control Presenter(s): [Lee] [Min] [Lee] [Lee]
[SIGGRAPH 2021]
![Low-cost SPAD sensing for non-line-of-sight tracking, material classification and depth imaging](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Callenberg_Low-Cost-SPAD-Sensing-for-Non-Line-Of-Sight-Tracking-Material-Classification-and-Depth-Imaging-150x150.jpg)
Low-cost SPAD sensing for non-line-of-sight tracking, material classification and depth imaging Presenter(s): [Callenberg] [Shi] [Heide] [Hullin]
[SIGGRAPH 2021]
![ManipNet: neural manipulation synthesis with a hand-object spatial representation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Zhang_ManipNet-Neural-Manipulation-Synthesis-with-a-Hand-Object-Spatial-Representation-150x150.jpg)
ManipNet: neural manipulation synthesis with a hand-object spatial representation Presenter(s): [Zhang] [Ye] [Shiratori] [Komura]
[SIGGRAPH 2021]
![Mechanics-aware deformation of yarn pattern geometry](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Sperl_Mechanics-Aware-Deformation-of-Yarn-Pattern-Geometry-150x150.jpg)
Mechanics-aware deformation of yarn pattern geometry Presenter(s): [Sperl] [Narain] [Wojtan]
[SIGGRAPH 2021]
![Medial IPC: accelerated incremental potential contact with medial elastics](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Lan_Medial-IPC-Accelerated-Incremental-Potential-Contact-with-Medial-Elastics-150x150.jpg)
Medial IPC: accelerated incremental potential contact with medial elastics Presenter(s): [Lan] [Yang] [Kaufman] [Yao] [Li] [Jiang]
[SIGGRAPH 2021]
![Mixture of volumetric primitives for efficient neural rendering](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Lombardi_Mixture-of-Volumetric-Primitives-for-Efficient-Neural-Rendering-150x150.jpg)
Mixture of volumetric primitives for efficient neural rendering Presenter(s): [Lombardi] [Simon] [Schwartz] [Zollhoefer] [Sheikh] [Saragih]
[SIGGRAPH 2021]
![MoCap-solver: a neural solver for optical motion capture data](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Chen_MoCap-Solver-A-Neural-Solver-for-Optical-Motion-Capture-Data-150x150.jpg)
MoCap-solver: a neural solver for optical motion capture data Presenter(s): [Chen] [Wang] [Zhang] [Xu] [Zhang] [Hu]
[SIGGRAPH 2021]
![MOCCA: modeling and optimizing cone-joints for complex assemblies](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Wang_MOCCA-Modeling-and-Optimizing-Cone-joints-for-Complex-Assemblies-150x150.jpg)
MOCCA: modeling and optimizing cone-joints for complex assemblies Presenter(s): [Wang] [Song] [Pauly]
[SIGGRAPH 2021]
![Modeling and fabrication with specified discrete equivalence classes](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Zhang_Modeling-and-Fabrication-with-Specified-Discrete-Equivalence-Classes-150x150.jpg)
Modeling and fabrication with specified discrete equivalence classes Presenter(s): [Liu] [Zhang] [Zhang] [Ye] [Liu] [Fu]
[SIGGRAPH 2021]
![Monte Carlo estimators for differential light transport](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Zeltner_Monte-Carlo-Estimators-for-Differential-Light-Transport-150x150.jpg)
Monte Carlo estimators for differential light transport Presenter(s): [Zeltner] [Speierer] [Georgiev] [Jakob]
[SIGGRAPH 2021]
![Multiscale cholesky preconditioning for ill-conditioned problems](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Chen_Multiscale-Cholesky-Preconditioning-for-Ill-conditioned-Problems-150x150.jpg)
Multiscale cholesky preconditioning for ill-conditioned problems Presenter(s): [Chen] [Schäfer] [Huang] [Desbrun]
[SIGGRAPH 2021]
![NeuMIP: multi-resolution neural materials](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Juznetsov_NeuMIP-Multi-Resolution-Neural-Materials-150x150.jpg)
NeuMIP: multi-resolution neural materials Presenter(s): [Kuznetsov] [Mullia] [Xu] [Hasan] [Ramamoorthi]
[SIGGRAPH 2021]
![Neural animation layering for synthesizing martial arts movements](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Starke_Neural-Animation-Layering-for-Synthesizing-Martial-Arts-Movements-150x150.jpg)
Neural animation layering for synthesizing martial arts movements Presenter(s): [Starke] [Zhao] [Zinno] [Komura]
[SIGGRAPH 2021]
![Neural complex luminaires: representation and rendering](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Zhu_Neural-Complex-Luminaires-Representation-and-Rendering-150x150.jpg)
Neural complex luminaires: representation and rendering Presenter(s): [Zhu] [Bai] [Xu] [Bako] [Velázquez-Armendáriz] [Wang] [Sen] [Hasan] [Yan]
[SIGGRAPH 2021]
![Neural monocular 3D human motion capture with physical awareness](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Shimada_Neural-Monocular-3D-Human-Motion-Capture-with-Physical-Awareness-150x150.jpg)
Neural monocular 3D human motion capture with physical awareness Presenter(s): [Shimada] [Golyanik] [Xu] [Perez] [Theobalt]
[SIGGRAPH 2021]
![Neural scene graph rendering](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Granskog_Neural-Scene-Graph-Rendering-150x150.jpg)
Neural scene graph rendering Presenter(s): [Granskog] [Schnabel] [Rousselle] [Novák]
[SIGGRAPH 2021]
![Only a matter of style: age transformation using a style-based regression model](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Alaluf_Only-a-Matter-of-Style-Age-Transformation-Using-a-Style-Based-Regression-Model-150x150.jpg)
Only a matter of style: age transformation using a style-based regression model Presenter(s): [Alaluf] [Patashnik] [Cohen-Or]
[SIGGRAPH 2021]
![Optimizing UI layouts for deformable face-rig manipulation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Kim_Optimizing-UI-Layouts-for-Deformable-Face-Rig-Manipulation-150x150.jpg)
Optimizing UI layouts for deformable face-rig manipulation Presenter(s): [Kim] [Singh]
[SIGGRAPH 2021]
![Orienting point clouds with dipole propagation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Metzer_Orienting-Point-Clouds-with-Dipole-Propagation-150x150.jpg)
Orienting point clouds with dipole propagation Presenter(s): [Metzer] [Hanocka] [Zorin] [Giryes] [Panozzo] [Cohen-Or]
[SIGGRAPH 2021]
![Pareto gamuts: exploring optimal designs across varying contexts](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Makatura_Pareto-Gamuts-Exploring-Optimal-Designs-Across-Varying-Contexts-150x150.jpg)
Pareto gamuts: exploring optimal designs across varying contexts Presenter(s): [Makatura] [Guo] [Schulz] [Solomon] [Matusik]
[SIGGRAPH 2021]
![Path replay backpropagation: differentiating light paths using constant memory and linear time](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Vicini_Path-Replay-Backpropagation_-Differentiating-Light-Paths-using-Constant-Memory-and-Linear-Time-150x150.jpg)
Path replay backpropagation: differentiating light paths using constant memory and linear time Presenter(s): [Vicini] [Speierer] [Jakob]
[SIGGRAPH 2021]
![Path-space differentiable rendering of participating media](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Zhang_Path-Space-Differentiable-Rendering-of-Participating-Media-150x150.jpg)
Path-space differentiable rendering of participating media Presenter(s): [Zhang] [Yu] [Zhao]
[SIGGRAPH 2021]
![PH-CPF: planar hexagonal meshing using coordinate power fields](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Pluta_PH-CPF-Planar-Hexagonal-Meshing-using-Coordinate-Power-Fields-150x150.jpg)
PH-CPF: planar hexagonal meshing using coordinate power fields Presenter(s): [Pluta] [Edelstein] [Vaxman] [Ben-Chen]
[SIGGRAPH 2021]
![PhotoApp: photorealistic appearance editing of head portraits](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Tewari_PhotoApp-Photorealistic-Appearance-Editing-of-Head-Portraits-150x150.jpg)
PhotoApp: photorealistic appearance editing of head portraits Presenter(s): [R.] [Tewari] [Dib] [Weyrich] [Bickel] [Seidel] [Pfister] [Matusik] [Elgharib] [Theobalt]
[SIGGRAPH 2021]
![Physical validation of simulators in computer graphics: a new framework dedicated to slender elastic structures and frictional contact](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Romero_Physical-validation-of-simulators-in-Computer-Graphics_-A-new-framework-dedicated-to-slender-elastic-structures-and-frictional-contact-150x150.jpg)
Physical validation of simulators in computer graphics: a new framework dedicated to slender elastic structures and frictional contact Presenter(s): [Romero] [Ly] [Rasheed] [Charrondière] [Lazarus] [Neukirch] [Bertails-Descoubes]
[SIGGRAPH 2021]
![QuanTaichi: a compiler for quantized simulations](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Hu_QuanTaichi-A-Compiler-for-Quantized-Simulations-150x150.jpg)
QuanTaichi: a compiler for quantized simulations Presenter(s): [Hu] [Liu] [Yang] [Xu] [Kuang] [Xu] [Dai] [Freeman] [Durand]
[SIGGRAPH 2021]
![Real-time 3D neural facial animation from binocular video](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Cao_Real-time-3D-Neural-Facial-Animation-from-Binocular-Video-150x150.jpg)
Real-time 3D neural facial animation from binocular video Presenter(s): [Cao] [Agrawal] [Torre] [Chen] [Saragih] [Simon] [Sheikh]
[SIGGRAPH 2021]
![Real-time deep dynamic characters](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Habermann_Real-time-Deep-Dynamic-Characters-150x150.jpg)
Real-time deep dynamic characters Presenter(s): [Habermann] [Liu] [Xu] [Zollhoefer] [Pons-Moll] [Theobalt]
[SIGGRAPH 2021]
![Real-time locally injective volumetric deformation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Liao_Real-time-Locally-Injective-Volumetric-Deformation-150x150.jpg)
Real-time locally injective volumetric deformation Organizer(s): [Liao] [Chen] [Hua] [Liu] [Weber]
[SIGGRAPH 2021]
![Real-time neural radiance caching for path tracing](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Muller_Real-time-Neural-Radiance-Caching-for-Path-Tracing-150x150.jpg)
Real-time neural radiance caching for path tracing Presenter(s): [Müller] [Rousselle] [Novák] [Keller]
[SIGGRAPH 2021]
![Reliable feature-line driven quad-remeshing](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Pietroni_Reliable-Feature-Line-Driven-Quad-Remeshing-150x150.jpg)
Reliable feature-line driven quad-remeshing Presenter(s): [Pietroni] [Nuvoli] [Alderighi] [Cignoni] [Tarini]
[SIGGRAPH 2021]
![Revisiting integration in the material point method: a scheme for easier separation and less dissipation](https://history.siggraph.org/wp-content/uploads/2022/05/SIGGRAPH2021_Image-Not-Available-150x150.jpg)
Revisiting integration in the material point method: a scheme for easier separation and less dissipation Presenter(s): [Fei] [Wu]
[SIGGRAPH 2021]
![ROSEFusion: random optimization for online dense reconstruction under fast camera motion](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Zhang_ROSEFusion-Random-Optimization-for-Online-Dense-Reconstruction-under-Fast-Camera-Motion-150x150.jpg)
ROSEFusion: random optimization for online dense reconstruction under fast camera motion Presenter(s): [Zhang] [Zhu] [Zheng] [Xu]
[SIGGRAPH 2021]
![SANM: a symbolic asymptotic numerical solver with applications in mesh deformation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Jia_SANM-A-Symbolic-Asymptotic-Numerical-Solver-with-Applications-in-Mesh-Deformation-150x150.jpg)
SANM: a symbolic asymptotic numerical solver with applications in mesh deformation Presenter(s): [Jia]
[SIGGRAPH 2021]
![Scalable image-based indoor scene rendering with reflections](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Xu_Scalable-Image-based-Indoor-Scene-Rendering-with-Reflections-150x150.jpg)
Scalable image-based indoor scene rendering with reflections Presenter(s): [Xu] [Wu] [Zu] [Huang] [Yang] [Bao] [Xu]
[SIGGRAPH 2021]
![Seamless manga inpainting with semantics awareness](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Xie_Seamless-Manga-Inpainting-with-Semantics-Awareness-150x150.jpg)
Seamless manga inpainting with semantics awareness Presenter(s): [Xie] [Xia] [Li] [Wong]
[SIGGRAPH 2021]
![ShapeMOD: macro operation discovery for 3D shape programs](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Jones_ShapeMOD-Macro-Operation-Discovery-for-3D-Shape-Programs-150x150.jpg)
ShapeMOD: macro operation discovery for 3D shape programs Presenter(s): [Jones] [Charatan] [Guerrero] [Mitra] [Ritchie]
[SIGGRAPH 2021]
![Solid-fluid interaction with surface-tension-dominant contact](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Ruan_Solid-Fluid-Interaction-with-Surface-Tension-Dominant-Contact-150x150.jpg)
Solid-fluid interaction with surface-tension-dominant contact Presenter(s): [Ruan] [Liu] [Zhu] [Sueda] [Wang] [Chen]
[SIGGRAPH 2021]
![SP-GAN: sphere-guided 3D shape generation and manipulation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Li_SP-GAN_-Sphere-Guided-3D-Shape-Generation-and-Manipulation-150x150.jpg)
SP-GAN: sphere-guided 3D shape generation and manipulation Presenter(s): [Li] [Li] [Hui] [Fu]
[SIGGRAPH 2021]
![StrokeStrip: joint parameterization and fitting of stroke clusters](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Mossel_StrokeStrip_-Joint-Parameterization-and-Fitting-of-Stroke-Clusters-150x150.jpg)
StrokeStrip: joint parameterization and fitting of stroke clusters Presenter(s): [Van Mossel] [Liu] [Vining] [Bessmeltsev] [Sheffer]
[SIGGRAPH 2021]
![StyleCariGAN: caricature generation via StyleGAN feature map modulation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Jang_StyleCariGAN_-Caricature-Generation-via-StyleGAN-Feature-Map-Modulation-150x150.jpg)
StyleCariGAN: caricature generation via StyleGAN feature map modulation Presenter(s): [Jang] [Ju] [Jung] [Yang] [Tong] [Lee]
[SIGGRAPH 2021]
![Surface multigrid via intrinsic prolongation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Liu_Surface-Multigrid-via-Intrinsic-Prolongation-150x150.jpg)
Surface multigrid via intrinsic prolongation Presenter(s): [Liu] [Zhang] [Ben-Chen] [Jacobson]
[SIGGRAPH 2021]
![SWAGAN: a style-based wavelet-driven generative model](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Gal_SWAGAN-A-Style-based-WAvelet-driven-Generative-Model-150x150.jpg)
SWAGAN: a style-based wavelet-driven generative model Presenter(s): [Gal] [Hochberg] [Bermano] [Cohen-Or]
[SIGGRAPH 2021]
![Swept volumes via spacetime numerical continuation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Sallan_Swept-Volumes-via-Spacetime-Numerical-Continuation-150x150.jpg)
Swept volumes via spacetime numerical continuation Presenter(s): [Sellán] [Aigerman] [Jacobson]
[SIGGRAPH 2021]
![Systematically differentiating parametric discontinuities](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Bangaru_Systematically-Differentiating-Parametric-Discontinuities-150x150.jpg)
Systematically differentiating parametric discontinuities Presenter(s): [Bangaru] [Michel] [Mu] [Bernstein] [Li] [Ragan-Kelley]
[SIGGRAPH 2021]
![The effect of shape and illumination on material perception: model and applications](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Serrano_The-effect-of-shape-and-illumination-on-material-perception-model-and-applications-150x150.jpg)
The effect of shape and illumination on material perception: model and applications Presenter(s): [Serrano] [Chen] [Wang] [Piovarči] [Seidel] [Didyk] [Myszkowski]
[SIGGRAPH 2021]
![The shape matching element method: direct animation of curved surface models](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Trusty_High-order-Differentiable-Autoencoder-for-Nonlinear-Model-Reduction-150x150.jpg)
The shape matching element method: direct animation of curved surface models Presenter(s): [Trusty] [Chen] [Levin]
[SIGGRAPH 2021]
![Thin-film smoothed particle hydrodynamics fluid](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Wang_Thin-Film-Smoothed-Particle-Hydrodynamics-Fluid-150x150.jpg)
Thin-film smoothed particle hydrodynamics fluid Presenter(s): [Wang] [Deng] [Kong] [Prasad] [Xiong] [Zhu]
[SIGGRAPH 2021]
![Total relighting: learning to relight portraits for background replacement](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Pandey_Total-Relighting-Learning-to-Relight-Portraits-for-Background-Replacement-150x150.jpg)
Total relighting: learning to relight portraits for background replacement Presenter(s): [Pandey] [Orts-Escolano] [LeGendre] [Haene] [Bouaziz] [Rhemann] [Debevec] [Fanello]
[SIGGRAPH 2021]
![Tracing versus freehand for evaluating computer-generated drawings](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Wang_Tracing-Versus-Freehand-for-Evaluating-Computer-Generated-Drawings-150x150.jpg)
Tracing versus freehand for evaluating computer-generated drawings Presenter(s): [Wang] [Qju] [Feng] [Rushmeier] [McMillan] [Dorsey]
[SIGGRAPH 2021]
![Transfer matrix based layered materials rendering](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Callet_Transfer-matrix-based-layered-materials-rendering-150x150.jpg)
Transfer matrix based layered materials rendering Presenter(s): [Randrianandrasana] [Callet] [Lucas]
[SIGGRAPH 2021]
![TransPose: real-time 3D human translation and pose estimation with six inertial sensors](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Yi_TransPose-Real-time-3D-Human-Translation-and-Pose-Estimation-with-Six-Inertial-Sensors-150x150.jpg)
TransPose: real-time 3D human translation and pose estimation with six inertial sensors Presenter(s): [Yi] [Zhou] [Xu]
[SIGGRAPH 2021]
![TryOnGAN: body-aware try-on via layered interpolation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Lewis_TryOnGAN-Body-Aware-Try-On-via-Layered-Interpolation-150x150.jpg)
TryOnGAN: body-aware try-on via layered interpolation Presenter(s): [Lewis] [Varadharajan] [Kemelmacher-Shlizerman]
[SIGGRAPH 2021]
![Unified particle system for multiple-fluid flow and porous material](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Ren_Unified-Particle-System-for-Multiple-fluid-Flow-and-Porous-Material-150x150.jpg)
Unified particle system for multiple-fluid flow and porous material Presenter(s): [Ren] [Xu] [Li]
[SIGGRAPH 2021]
![Unsupervised learning for cuboid shape abstraction via joint segmentation from point clouds](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Yang_Unsupervised-Learning-for-Cuboid-Shape-Abstraction-via-Joint-Segmentation-from-Point-Clouds-150x150.jpg)
Unsupervised learning for cuboid shape abstraction via joint segmentation from point clouds Presenter(s): [Yang] [Chen]
[SIGGRAPH 2021]
![Using isometries for computational design and fabrication](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Jiang_Using-isometries-for-computational-design-and-fabrication-150x150.jpg)
Using isometries for computational design and fabrication Presenter(s): [Jiang] [Wang] [Inza] [Dellinger] [Rist] [Wallner] [Pottmann]
[SIGGRAPH 2021]
![Video recoloring via spatial-temporal geometric palettes](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Du_Video-Recoloring-via-Spatial-Temporal-Geometric-Palettes-150x150.jpg)
Video recoloring via spatial-temporal geometric palettes Presenter(s): [Du] [Lei] [Xu] [Tan] [Gingold]
[SIGGRAPH 2021]
![Volumetric appearance stylization with stylizing kernel prediction network](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Guo_Volumetric-Appearance-Stylization-with-Stylizing-Kernel-Prediction-Network-150x150.jpg)
Volumetric appearance stylization with stylizing kernel prediction network Presenter(s): [Guo] [Li] [Zong] [Liu] [He] [Guo] [Yan]
[SIGGRAPH 2021]
![Weakly-supervised contrastive learning in path manifold for Monte Carlo image reconstruction](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Cho_Weakly-Supervised-Contrastive-Learning-in-Path-Manifold-for-Monte-Carlo-Image-Reconstruction-150x150.jpg)
Weakly-supervised contrastive learning in path manifold for Monte Carlo image reconstruction Presenter(s): [Cho] [Huo] [Yoon]
[SIGGRAPH 2021]
![Total relighting: learning to relight portraits for background replacement](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Pandey_Total-Relighting-Learning-to-Relight-Portraits-for-Background-Replacement-150x150.jpg)
Total relighting: learning to relight portraits for background replacement Presenter(s): [Pandey] [Orts-Escolano] [LeGendre] [Haene] [Bouaziz] [Rhemann] [Debevec] [Fanello]
[SIGGRAPH 2021]
![Interactive modelling of volumetric musculoskeletal anatomy](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Bang_Interactive-Modelling-of-Volumetric-Musculoskeletal-Anatomy-150x150.jpg)
Interactive modelling of volumetric musculoskeletal anatomy Presenter(s): [Abdrashitov] [Bang] [Levin] [Singh] [Jacobson]
[SIGGRAPH 2021]
![Only a matter of style: age transformation using a style-based regression model](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Alaluf_Only-a-Matter-of-Style-Age-Transformation-Using-a-Style-Based-Regression-Model-150x150.jpg)
Only a matter of style: age transformation using a style-based regression model Presenter(s): [Alaluf] [Patashnik] [Cohen-Or]
[SIGGRAPH 2021]
![Driving-signal aware full-body avatars](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Wu_Driving-Signal-Aware-Full-Body-Avatars-150x150.jpg)
Driving-signal aware full-body avatars Presenter(s): [Bagautdinov] [Wu] [Simon] [Prada] [Shiratori] [Wei] [Xu] [Sheikh] [Saragih]
[SIGGRAPH 2021]
![Systematically differentiating parametric discontinuities](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Bangaru_Systematically-Differentiating-Parametric-Discontinuities-150x150.jpg)
Systematically differentiating parametric discontinuities Presenter(s): [Bangaru] [Michel] [Mu] [Bernstein] [Li] [Ragan-Kelley]
[SIGGRAPH 2021]
![Geometry and tool motion planning for curvature adapted CNC machining](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Barton_Geometry-and-tool-motion-planning-for-curvature-adapted-CNC-machining-150x150.jpg)
Geometry and tool motion planning for curvature adapted CNC machining Presenter(s): [Barton] [Bizzarri] [Rist] [Sliusarenko] [Pottmann]
[SIGGRAPH 2021]
![An inverse method for the exploration of layered material appearance](https://history.siggraph.org/wp-content/uploads/2022/05/SIGGRAPH2021_Image-Not-Available-150x150.jpg)
An inverse method for the exploration of layered material appearance Presenter(s): [Bati] [Barla] [Pacanowski]
[SIGGRAPH 2021]
![Deep relightable appearance models for animatable faces](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Bi_Deep-Relightable-Appearance-Models-for-Animatable-Faces-150x150.jpg)
Deep relightable appearance models for animatable faces Presenter(s): [Bi] [Lombardi] [Saito] [Simon] [Wei] [Mcphail] [Ramamoorthi] [Sheikh] [Saragih]
[SIGGRAPH 2021]
![WRAPD: weighted rotation-aware ADMM for parameterization and deformation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Brown_WRAPD-Weighted-Rotation-aware-ADMM-for-Parameterization-and-Deformation-150x150.jpg)
WRAPD: weighted rotation-aware ADMM for parameterization and deformation Presenter(s): [Brown] [Narain]
[SIGGRAPH 2021]
![A time-independent deformer for elastic contacts](https://history.siggraph.org/wp-content/uploads/2022/05/SIGGRAPH2021_Image-Not-Available-150x150.jpg)
A time-independent deformer for elastic contacts Presenter(s): [Brunel] [Bénard] [Guennebaud]
[SIGGRAPH 2021]
![Displaced signed distance fields for additive manufacturing](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Brunton_Displaced-Signed-Distance-Fields-for-Additive-Manufacturing-150x150.jpg)
Displaced signed distance fields for additive manufacturing Presenter(s): [Brunton] [Rmaileh]
[SIGGRAPH 2021]
![Low-cost SPAD sensing for non-line-of-sight tracking, material classification and depth imaging](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Callenberg_Low-Cost-SPAD-Sensing-for-Non-Line-Of-Sight-Tracking-Material-Classification-and-Depth-Imaging-150x150.jpg)
Low-cost SPAD sensing for non-line-of-sight tracking, material classification and depth imaging Presenter(s): [Callenberg] [Shi] [Heide] [Hullin]
[SIGGRAPH 2021]
![Real-time 3D neural facial animation from binocular video](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Cao_Real-time-3D-Neural-Facial-Animation-from-Binocular-Video-150x150.jpg)
Real-time 3D neural facial animation from binocular video Presenter(s): [Cao] [Agrawal] [Torre] [Chen] [Saragih] [Simon] [Sheikh]
[SIGGRAPH 2021]
![A momentum-conserving implicit material point method for surface tension with contact angles and spatial gradients](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Chen_A-Momentum-Conserving-Implicit-Material-Point-Method-for-Surface-Tension-with-Contact-Angles-and-Spatial-Gradients-150x150.jpg)
A momentum-conserving implicit material point method for surface tension with contact angles and spatial gradients Presenter(s): [Chen] [Kala] [Marquez-Razon] [Gueidon] [Hyde] [Teran]
[SIGGRAPH 2021]
![Bistable auxetic surface structures](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Chen_Bistable-Auxetic-Surface-Structures-150x150.jpg)
Bistable auxetic surface structures Presenter(s): [Chen] [Panetta] [Schnaubelt] [Pauly]
[SIGGRAPH 2021]
![Capturing detailed deformations of moving human bodies](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Chen_Capturing-Detailed-Deformations-of-Moving-Human-Bodies-150x150.jpg)
Capturing detailed deformations of moving human bodies Presenter(s): [Chen] [Park] [Macit] [Kavan]
[SIGGRAPH 2021]
![ChoreoMaster: choreography-oriented music-driven dance synthesis](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Chen_ChoreoMaster_-Choreography-Oriented-Music-Driven-Dance-Synthesis-150x150.jpg)
ChoreoMaster: choreography-oriented music-driven dance synthesis Presenter(s): [Chen] [Tand] [Lei] [Zhang] [Guo] [Zhang] [Hu]
[SIGGRAPH 2021]
![DeepFaceEditing: deep face generation and editing with disentangled geometry and appearance control](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Chen_DeepFaceEditing-Deep-Face-Generation-and-Editing-with-Disentangled-Geometry-and-Appearance-Control-150x150.jpg)
DeepFaceEditing: deep face generation and editing with disentangled geometry and appearance control Presenter(s): [Chen] [Liu] [Lai] [Rosin] [Li] [Fu] [Gao]
[SIGGRAPH 2021]
![MoCap-solver: a neural solver for optical motion capture data](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Chen_MoCap-Solver-A-Neural-Solver-for-Optical-Motion-Capture-Data-150x150.jpg)
MoCap-solver: a neural solver for optical motion capture data Presenter(s): [Chen] [Wang] [Zhang] [Xu] [Zhang] [Hu]
[SIGGRAPH 2021]
![Multiscale cholesky preconditioning for ill-conditioned problems](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Chen_Multiscale-Cholesky-Preconditioning-for-Ill-conditioned-Problems-150x150.jpg)
Multiscale cholesky preconditioning for ill-conditioned problems Presenter(s): [Chen] [Schäfer] [Huang] [Desbrun]
[SIGGRAPH 2021]
![Weakly-supervised contrastive learning in path manifold for Monte Carlo image reconstruction](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Cho_Weakly-Supervised-Contrastive-Learning-in-Path-Manifold-for-Monte-Carlo-Image-Reconstruction-150x150.jpg)
Weakly-supervised contrastive learning in path manifold for Monte Carlo image reconstruction Presenter(s): [Cho] [Huo] [Yoon]
[SIGGRAPH 2021]
![Learning meaningful controls for fluids](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Chu_Learning-Meaningful-Controls-for-Fluids-150x150.jpg)
Learning meaningful controls for fluids Presenter(s): [Chu] [Thuerey] [Seidel] [Theobalt] [Zayer]
[SIGGRAPH 2021]
![Boundary-sampled halfspaces: a new representation for constructive solid modeling](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Du_Boundary-Sampled-Halfspaces-A-New-Representation-for-Constructive-Solid-Modeling-150x150.jpg)
Boundary-sampled halfspaces: a new representation for constructive solid modeling Presenter(s): [Du] [Zhou] [Carr] [Ju]
[SIGGRAPH 2021]
![Video recoloring via spatial-temporal geometric palettes](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Du_Video-Recoloring-via-Spatial-Temporal-Geometric-Palettes-150x150.jpg)
Video recoloring via spatial-temporal geometric palettes Presenter(s): [Du] [Lei] [Xu] [Tan] [Gingold]
[SIGGRAPH 2021]
![Authoring consistent landscapes with flora and fauna](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Carrez_Authoring-Consistent-Landscapes-with-Flora-and-Fauna-150x150.jpg)
Authoring consistent landscapes with flora and fauna Presenter(s): [Ecormier-Nocca] [Cordonnier] [Carrez] [Moigne] [Memari] [Benes] [Cani]
[SIGGRAPH 2021]
![Guaranteed globally injective 3D deformation processing](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Fang_Guaranteed-Globally-Injective-3D-Deformation-Processing-150x150.jpg)
Guaranteed globally injective 3D deformation processing Presenter(s): [Fang] [Li] [Jiang] [Kaufman]
[SIGGRAPH 2021]
![Revisiting integration in the material point method: a scheme for easier separation and less dissipation](https://history.siggraph.org/wp-content/uploads/2022/05/SIGGRAPH2021_Image-Not-Available-150x150.jpg)
Revisiting integration in the material point method: a scheme for easier separation and less dissipation Presenter(s): [Fei] [Wu]
[SIGGRAPH 2021]
![Learning an animatable detailed 3D face model from in-the-wild images](https://history.siggraph.org/wp-content/uploads/2022/05/SIGGRAPH2021_Image-Not-Available-150x150.jpg)
Learning an animatable detailed 3D face model from in-the-wild images Presenter(s): [Feng] [Feng] [Black] [Bolkart]
[SIGGRAPH 2021]
![Intersection-free rigid body dynamics](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Ferguson_Intersection-free-Rigid-Body-Dynamics-150x150.jpg)
Intersection-free rigid body dynamics Presenter(s): [Ferguson] [Li] [Schneider] [Ureta] [Langlois] [Jiang] [Zorin] [Kaufman] [Panozzo]
[SIGGRAPH 2021]
![SWAGAN: a style-based wavelet-driven generative model](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Gal_SWAGAN-A-Style-based-WAvelet-driven-Generative-Model-150x150.jpg)
SWAGAN: a style-based wavelet-driven generative model Presenter(s): [Gal] [Hochberg] [Bermano] [Cohen-Or]
[SIGGRAPH 2021]
![Foldover-free maps in 50 lines of code](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Garanzha_Foldover-free-maps-in-50-lines-of-code-150x150.jpg)
Foldover-free maps in 50 lines of code Presenter(s): [Garanzha] [Kaporin] [Kudryavtseva] [Protais] [Ray] [Sokolov]
[SIGGRAPH 2021]
![Discrete conformal equivalence of polyhedral surfaces](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Gillespie_Discrete-Conformal-Equivalence-of-Polyhedral-Surfaces-150x150.jpg)
Discrete conformal equivalence of polyhedral surfaces Presenter(s): [Gillespie] [Springborn] [Crane]
[SIGGRAPH 2021]
![Neural scene graph rendering](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Granskog_Neural-Scene-Graph-Rendering-150x150.jpg)
Neural scene graph rendering Presenter(s): [Granskog] [Schnabel] [Rousselle] [Novák]
[SIGGRAPH 2021]
![Highlight-aware two-stream network for single-image SVBRDF acquisition](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Guo_Highlight-Aware-Two-Stream-Network-for-Single-Image-SVBRDF-Acquisition-150x150.jpg)
Highlight-aware two-stream network for single-image SVBRDF acquisition Presenter(s): [Guo] [Lai] [Tao] [Cai] [Wang] [Guo] [Yan]
[SIGGRAPH 2021]
![Volumetric appearance stylization with stylizing kernel prediction network](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Guo_Volumetric-Appearance-Stylization-with-Stylizing-Kernel-Prediction-Network-150x150.jpg)
Volumetric appearance stylization with stylizing kernel prediction network Presenter(s): [Guo] [Li] [Zong] [Liu] [He] [Guo] [Yan]
[SIGGRAPH 2021]
![Real-time deep dynamic characters](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Habermann_Real-time-Deep-Dynamic-Characters-150x150.jpg)
Real-time deep dynamic characters Presenter(s): [Habermann] [Liu] [Xu] [Zollhoefer] [Pons-Moll] [Theobalt]
[SIGGRAPH 2021]
![Fire in paradise: mesoscale simulation of wildfires](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Hadrich_Fire-in-Paradise1-Mesoscale-Simulation-of-Wildfires-150x150.jpg)
Fire in paradise: mesoscale simulation of wildfires Presenter(s): [Hädrich] [Banuti] [Palubicki] [Pirk] [Michels]
[SIGGRAPH 2021]
![Endless loops: detecting and animating periodic patterns in still images](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Halperin_Endless-Loops-Detecting-and-Animating-Periodic-Patterns-in-Still-Images-150x150.jpg)
Endless loops: detecting and animating periodic patterns in still images Presenter(s): [Halperin] [Hakim] [Vantzos] [Hochman] [Benaim] [Sassy] [Kupchik] [Bibi] [Fried]
[SIGGRAPH 2021]
![QuanTaichi: a compiler for quantized simulations](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Hu_QuanTaichi-A-Compiler-for-Quantized-Simulations-150x150.jpg)
QuanTaichi: a compiler for quantized simulations Presenter(s): [Hu] [Liu] [Yang] [Xu] [Kuang] [Xu] [Dai] [Freeman] [Durand]
[SIGGRAPH 2021]
![Designing actuation systems for animatronic figures via globally optimal discrete search](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Huber_Designing-actuation-systems-for-animatronic-figures-via-globally-optimal-discrete-search-150x150.jpg)
Designing actuation systems for animatronic figures via globally optimal discrete search Presenter(s): [Huber] [Poranne] [Coros]
[SIGGRAPH 2021]
![Interactive Monte Carlo denoising using affinity of neural features](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Isik_Interactive-Monte-Carlo-Denoising-using-Affinity-of-Neural-Features-150x150.jpg)
Interactive Monte Carlo denoising using affinity of neural features Presenter(s): [Işık] [Mullia] [Fisher] [Eisenmann] [Gharbi]
[SIGGRAPH 2021]
![StyleCariGAN: caricature generation via StyleGAN feature map modulation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Jang_StyleCariGAN_-Caricature-Generation-via-StyleGAN-Feature-Map-Modulation-150x150.jpg)
StyleCariGAN: caricature generation via StyleGAN feature map modulation Presenter(s): [Jang] [Ju] [Jung] [Yang] [Tong] [Lee]
[SIGGRAPH 2021]
![SANM: a symbolic asymptotic numerical solver with applications in mesh deformation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Jia_SANM-A-Symbolic-Asymptotic-Numerical-Solver-with-Applications-in-Mesh-Deformation-150x150.jpg)
SANM: a symbolic asymptotic numerical solver with applications in mesh deformation Presenter(s): [Jia]
[SIGGRAPH 2021]
![Bijective and coarse high-order tetrahedral meshes](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Jiang_Bijective-and-Coarse-High-Order-Tetrahedral-Meshes-150x150.jpg)
Bijective and coarse high-order tetrahedral meshes Presenter(s): [Jiang] [Zhang] [Hu] [Schneider] [Zorin] [Panozzo]
[SIGGRAPH 2021]
![Using isometries for computational design and fabrication](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Jiang_Using-isometries-for-computational-design-and-fabrication-150x150.jpg)
Using isometries for computational design and fabrication Presenter(s): [Jiang] [Wang] [Inza] [Dellinger] [Rist] [Wallner] [Pottmann]
[SIGGRAPH 2021]
![ShapeMOD: macro operation discovery for 3D shape programs](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Jones_ShapeMOD-Macro-Operation-Discovery-for-3D-Shape-Programs-150x150.jpg)
ShapeMOD: macro operation discovery for 3D shape programs Presenter(s): [Jones] [Charatan] [Guerrero] [Mitra] [Ritchie]
[SIGGRAPH 2021]
![Knit sketching: from cut & sew patterns to machine-knit garments](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Kaspar_Knit-Sketching-from-Cut-_-Sew-Patterns-to-Machine-Knit-Garments-150x150.jpg)
Knit sketching: from cut & sew patterns to machine-knit garments Presenter(s): [Kaspar] [Wu] [Luo] [Makatura] [Matusik]
[SIGGRAPH 2021]
![Constrained projective dynamics: real-time simulation of deformable objects with energy-momentum conservation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Kee_Constrained-Projective-Dynamics_-Real-Time-Simulation-of-Deformable-Objects-with-Energy-Momentum-Conservation-150x150.jpg)
Constrained projective dynamics: real-time simulation of deformable objects with energy-momentum conservation Presenter(s): [Kee] [Um] [Jeong] [Han]
[SIGGRAPH 2021]
![An unbiased ray-marching transmittance estimator](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Kettunen_An-unbiased-ray-marching-transmittance-estimator-150x150.jpg)
An unbiased ray-marching transmittance estimator Presenter(s): [Kettunen] [d’Eon] [Pantaleoni] [Novák]
[SIGGRAPH 2021]
![Dynamic closest color warping to sort and compare palettes](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Kim_Dynamic-Closest-Color-Warping-to-Sort-and-Compare-Palettes-150x150.jpg)
Dynamic closest color warping to sort and compare palettes Presenter(s): [Kim] [Choi]
[SIGGRAPH 2021]
![Optimizing UI layouts for deformable face-rig manipulation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Kim_Optimizing-UI-Layouts-for-Deformable-Face-Rig-Manipulation-150x150.jpg)
Optimizing UI layouts for deformable face-rig manipulation Presenter(s): [Kim] [Singh]
[SIGGRAPH 2021]
![A perceptual model for eccentricity-dependent spatio-temporal flicker fusion and its applications to foveated graphics](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Krjancich_A-Perceptual-Model-for-Eccentricity-dependent-Spatio-temporal-Flicker-Fusion-and-its-Applications-to-Foveated-Graphics-150x150.jpg)
A perceptual model for eccentricity-dependent spatio-temporal flicker fusion and its applications to foveated graphics Presenter(s): [Krajancich] [Kellnhofer] [Wetzstein]
[SIGGRAPH 2021]
![NeuMIP: multi-resolution neural materials](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Juznetsov_NeuMIP-Multi-Resolution-Neural-Materials-150x150.jpg)
NeuMIP: multi-resolution neural materials Presenter(s): [Kuznetsov] [Mullia] [Xu] [Hasan] [Ramamoorthi]
[SIGGRAPH 2021]
![Medial IPC: accelerated incremental potential contact with medial elastics](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Lan_Medial-IPC-Accelerated-Incremental-Potential-Contact-with-Medial-Elastics-150x150.jpg)
Medial IPC: accelerated incremental potential contact with medial elastics Presenter(s): [Lan] [Yang] [Kaufman] [Yao] [Li] [Jiang]
[SIGGRAPH 2021]
![Direct delta mush skinning compression with continuous examples](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Le_Direct-Delta-Mush-Skinning-Compression-with-Continuous-Examples-150x150.jpg)
Direct delta mush skinning compression with continuous examples Presenter(s): [Le] [Villeneuve] [Gonzalez-Ochoa]
[SIGGRAPH 2021]
![A mathematical foundation for foundation paper pieceable quilts](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Leake_A-Mathematical-Foundation-for-Foundation-Paper-Pieceable-Quilts-150x150.jpg)
A mathematical foundation for foundation paper pieceable quilts Presenter(s): [Leake] [Bernstein] [Davis] [Agrawala]
[SIGGRAPH 2021]
![Learning a family of motor skills from a single motion clip](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Lee_Learning-a-family-of-motor-skills-from-a-single-motion-clip-150x150.jpg)
Learning a family of motor skills from a single motion clip Presenter(s): [Lee] [Lee] [Lee] [Lee]
[SIGGRAPH 2021]
![Learning time-critical responses for interactive character control](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Lee_Learning-Time-Critical-Responses-for-Interactive-Character-Control-150x150.jpg)
Learning time-critical responses for interactive character control Presenter(s): [Lee] [Min] [Lee] [Lee]
[SIGGRAPH 2021]
![TryOnGAN: body-aware try-on via layered interpolation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Lewis_TryOnGAN-Body-Aware-Try-On-via-Layered-Interpolation-150x150.jpg)
TryOnGAN: body-aware try-on via layered interpolation Presenter(s): [Lewis] [Varadharajan] [Kemelmacher-Shlizerman]
[SIGGRAPH 2021]
![SP-GAN: sphere-guided 3D shape generation and manipulation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Li_SP-GAN_-Sphere-Guided-3D-Shape-Generation-and-Manipulation-150x150.jpg)
SP-GAN: sphere-guided 3D shape generation and manipulation Presenter(s): [Li] [Li] [Hui] [Fu]
[SIGGRAPH 2021]
![Real-time locally injective volumetric deformation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Liao_Real-time-Locally-Injective-Volumetric-Deformation-150x150.jpg)
Real-time locally injective volumetric deformation Organizer(s): [Liao] [Chen] [Hua] [Liu] [Weber]
[SIGGRAPH 2021]
![Knitting 4D garments with elasticity controlled for body motion](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Liu_Knitting-4D-Garments-with-Elasticity-Controlled-for-Body-Motion-150x150.jpg)
Knitting 4D garments with elasticity controlled for body motion Presenter(s): [Liu] [Han] [Zhang] [Chen] [Lai] [Doubrovski] [Whiting] [Wang]
[SIGGRAPH 2021]
![Modeling and fabrication with specified discrete equivalence classes](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Zhang_Modeling-and-Fabrication-with-Specified-Discrete-Equivalence-Classes-150x150.jpg)
Modeling and fabrication with specified discrete equivalence classes Presenter(s): [Liu] [Zhang] [Zhang] [Ye] [Liu] [Fu]
[SIGGRAPH 2021]
![Surface multigrid via intrinsic prolongation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Liu_Surface-Multigrid-via-Intrinsic-Prolongation-150x150.jpg)
Surface multigrid via intrinsic prolongation Presenter(s): [Liu] [Zhang] [Ben-Chen] [Jacobson]
[SIGGRAPH 2021]
![Mixture of volumetric primitives for efficient neural rendering](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Lombardi_Mixture-of-Volumetric-Primitives-for-Efficient-Neural-Rendering-150x150.jpg)
Mixture of volumetric primitives for efficient neural rendering Presenter(s): [Lombardi] [Simon] [Schwartz] [Zollhoefer] [Sheikh] [Saragih]
[SIGGRAPH 2021]
![DiffAqua: a differentiable computational design pipeline for soft underwater swimmers with shape interpolation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Ma_DiffAqua-A-Differentiable-Computational-Design-Pipeline-for-Soft-Underwater-Swimmers-with-Shape-Interpolation-150x150.jpg)
DiffAqua: a differentiable computational design pipeline for soft underwater swimmers with shape interpolation Presenter(s): [Ma] [Du] [Zhang] [Wu] [Spielberg] [Katzschmann] [Matusik]
[SIGGRAPH 2021]
![Free-form scanning of non-planar appearance with neural trace photography](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Ma_Free-form-Scanning-of-Non-planar-Appearance-with-Neural-Trace-Photography-150x150.jpg)
Free-form scanning of non-planar appearance with neural trace photography Presenter(s): [Ma] [Kang] [Zhu] [Wu] [Zhou]
[SIGGRAPH 2021]
![Pareto gamuts: exploring optimal designs across varying contexts](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Makatura_Pareto-Gamuts-Exploring-Optimal-Designs-Across-Varying-Contexts-150x150.jpg)
Pareto gamuts: exploring optimal designs across varying contexts Presenter(s): [Makatura] [Guo] [Schulz] [Solomon] [Matusik]
[SIGGRAPH 2021]
![Guaranteed-quality higher-order triangular meshing of 2D domains](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Mandad_Guaranteed-Quality-Higher-Order-Triangular-Meshing-of-2D-Domains-150x150.jpg)
Guaranteed-quality higher-order triangular meshing of 2D domains Presenter(s): [Mandad] [Campen]
[SIGGRAPH 2021]
![FovVideoVDP: a visible difference predictor for wide field-of-view video](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Mantiuk_FovVideoVDP-A-visible-difference-predictor-for-wide-field-of-view-video-150x150.jpg)
FovVideoVDP: a visible difference predictor for wide field-of-view video Presenter(s): [Mantiuk] [Denes] [Chapiro] [Kaplayan] [Rufo] [Bachy] [Lian] [Patney]
[SIGGRAPH 2021]
![Acorn: adaptive coordinate networks for neural scene representation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Martel_acorn-Adaptive-Coordinate-Networks-for-Neural-Scene-Representation-150x150.jpg)
Acorn: adaptive coordinate networks for neural scene representation Presenter(s): [Martel] [Lindell] [Lin] [Chan] [Monteiro] [Wetzstein]
[SIGGRAPH 2021]
![Orienting point clouds with dipole propagation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Metzer_Orienting-Point-Clouds-with-Dipole-Propagation-150x150.jpg)
Orienting point clouds with dipole propagation Presenter(s): [Metzer] [Hanocka] [Zorin] [Giryes] [Panozzo] [Cohen-Or]
[SIGGRAPH 2021]
![DAG amendment for inverse control of parametric shapes](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Michel_DAG-Amendment-for-Inverse-Control-of-Parametric-Shapes-150x150.jpg)
DAG amendment for inverse control of parametric shapes Presenter(s): [Michel] [Boubekeur]
[SIGGRAPH 2021]
![General virtual sketching framework for vector line art](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Mo_General-Virtual-Sketching-Framework-for-Vector-Line-Art-150x150.jpg)
General virtual sketching framework for vector line art Presenter(s): [Mo] [Simo-Serra] [Gao] [Zou] [Wang]
[SIGGRAPH 2021]
![Real-time neural radiance caching for path tracing](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Muller_Real-time-Neural-Radiance-Caching-for-Path-Tracing-150x150.jpg)
Real-time neural radiance caching for path tracing Presenter(s): [Müller] [Rousselle] [Novák] [Keller]
[SIGGRAPH 2021]
![Kelvin transformations for simulations on infinite domains](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Nabizadeh_Kelvin-Transformations-for-Simulations-on-Infinite-Domains-150x150.jpg)
Kelvin transformations for simulations on infinite domains Presenter(s): [Nabizadeh] [Ramamoorthi] [Chern]
[SIGGRAPH 2021]
![KnitKit: a flexible system for machine knitting of customizable textiles](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Nadar_KnitKit-A-flexible-system-for-machine-knitting-of-customizable-textiles-150x150.jpg)
KnitKit: a flexible system for machine knitting of customizable textiles Presenter(s): [Nader] [Quek] [Chia] [Weeger] [Yeung]
[SIGGRAPH 2021]
![A gradient-based framework for 3D print appearance optimization](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Nindel_A-Gradient-Based-Framework-for-3D-Print-Appearance-Optimization-150x150.jpg)
A gradient-based framework for 3D print appearance optimization Presenter(s): [Nindel] [Iser] [Rittig] [Wilkie] [Křivánek]
[SIGGRAPH 2021]
![Computational inverse design of surface-based inflatables](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Panetta_Computational-Inverse-Design-of-Surface-based-Inflatables-150x150.jpg)
Computational inverse design of surface-based inflatables Presenter(s): [Panetta] [Isvoranu] [Chen] [Siéfert] [Roman] [Pauly]
[SIGGRAPH 2021]
![Computational design of weingarten surfaces](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Pellis_Computational-Design-of-Weingarten-Surfaces-150x150.jpg)
Computational design of weingarten surfaces Presenter(s): [Pellis] [Kilian] [Pottmann] [Pauly]
[SIGGRAPH 2021]
![AMP: adversarial motion priors for stylized physics-based character control](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Peng_AMP-Adversarial-Motion-Priors-for-Stylized-Physics-Based-Character-Control-150x150.jpg)
AMP: adversarial motion priors for stylized physics-based character control Presenter(s): [Peng] [Ma] [Abbeel] [Levine] [Kanazawa]
[SIGGRAPH 2021]
![Reliable feature-line driven quad-remeshing](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Pietroni_Reliable-Feature-Line-Driven-Quad-Remeshing-150x150.jpg)
Reliable feature-line driven quad-remeshing Presenter(s): [Pietroni] [Nuvoli] [Alderighi] [Cignoni] [Tarini]
[SIGGRAPH 2021]
![PH-CPF: planar hexagonal meshing using coordinate power fields](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Pluta_PH-CPF-Planar-Hexagonal-Meshing-using-Coordinate-Power-Fields-150x150.jpg)
PH-CPF: planar hexagonal meshing using coordinate power fields Presenter(s): [Pluta] [Edelstein] [Vaxman] [Ben-Chen]
[SIGGRAPH 2021]
![Fast linking numbers for topology verification of loopy structures](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-James_Fast-Linking-Numbers-for-Topology-Verification-of-Loopy-Structures-150x150.jpg)
Fast linking numbers for topology verification of loopy structures Presenter(s): [Qu] [James]
[SIGGRAPH 2021]
![PhotoApp: photorealistic appearance editing of head portraits](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Tewari_PhotoApp-Photorealistic-Appearance-Editing-of-Head-Portraits-150x150.jpg)
PhotoApp: photorealistic appearance editing of head portraits Presenter(s): [R.] [Tewari] [Dib] [Weyrich] [Bickel] [Seidel] [Pfister] [Matusik] [Elgharib] [Theobalt]
[SIGGRAPH 2021]
![Transfer matrix based layered materials rendering](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Callet_Transfer-matrix-based-layered-materials-rendering-150x150.jpg)
Transfer matrix based layered materials rendering Presenter(s): [Randrianandrasana] [Callet] [Lucas]
[SIGGRAPH 2021]
![3D weaving with curved ribbons](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Ren_3D-Weaving-with-Curved-Ribbons-150x150.jpg)
3D weaving with curved ribbons Presenter(s): [Ren] [Panetta] [Chen] [Isvoranu] [Poincloux] [Brandt] [Martin] [Pauly]
[SIGGRAPH 2021]
![Unified particle system for multiple-fluid flow and porous material](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Ren_Unified-Particle-System-for-Multiple-fluid-Flow-and-Porous-Material-150x150.jpg)
Unified particle system for multiple-fluid flow and porous material Presenter(s): [Ren] [Xu] [Li]
[SIGGRAPH 2021]
![Learning contact corrections for handle-based subspace dynamics](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Romero_Learning-Contact-Corrections-for-Handle-Based-Subspace-Dynamics-150x150.jpg)
Learning contact corrections for handle-based subspace dynamics Presenter(s): [Romero] [Casas] [Rodríguez] [Otaduy]
[SIGGRAPH 2021]
![Physical validation of simulators in computer graphics: a new framework dedicated to slender elastic structures and frictional contact](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Romero_Physical-validation-of-simulators-in-Computer-Graphics_-A-new-framework-dedicated-to-slender-elastic-structures-and-frictional-contact-150x150.jpg)
Physical validation of simulators in computer graphics: a new framework dedicated to slender elastic structures and frictional contact Presenter(s): [Romero] [Ly] [Rasheed] [Charrondière] [Lazarus] [Neukirch] [Bertails-Descoubes]
[SIGGRAPH 2021]
![Solid-fluid interaction with surface-tension-dominant contact](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Ruan_Solid-Fluid-Interaction-with-Surface-Tension-Dominant-Contact-150x150.jpg)
Solid-fluid interaction with surface-tension-dominant contact Presenter(s): [Ruan] [Liu] [Zhu] [Sueda] [Wang] [Chen]
[SIGGRAPH 2021]
![Fast diffraction pathfinding for dynamic sound propagation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Schissler_Fast-Diffraction-Pathfinding-for-Dynamic-Sound-Propagation-150x150.jpg)
Fast diffraction pathfinding for dynamic sound propagation Presenter(s): [Schissler] [Mückl] [Calamia]
[SIGGRAPH 2021]
![Swept volumes via spacetime numerical continuation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Sallan_Swept-Volumes-via-Spacetime-Numerical-Continuation-150x150.jpg)
Swept volumes via spacetime numerical continuation Presenter(s): [Sellán] [Aigerman] [Jacobson]
[SIGGRAPH 2021]
![The effect of shape and illumination on material perception: model and applications](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Serrano_The-effect-of-shape-and-illumination-on-material-perception-model-and-applications-150x150.jpg)
The effect of shape and illumination on material perception: model and applications Presenter(s): [Serrano] [Chen] [Wang] [Piovarči] [Seidel] [Didyk] [Myszkowski]
[SIGGRAPH 2021]
![High-order differentiable autoencoder for nonlinear model reduction](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Shen_High-order-Differentiable-Autoencoder-for-Nonlinear-Model-Reduction-150x150.jpg)
High-order differentiable autoencoder for nonlinear model reduction Presenter(s): [Shen] [Yang] [Shao] [Wang] [Jiang] [Lan] [Zhou]
[SIGGRAPH 2021]
![Neural monocular 3D human motion capture with physical awareness](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Shimada_Neural-Monocular-3D-Human-Motion-Capture-with-Physical-Awareness-150x150.jpg)
Neural monocular 3D human motion capture with physical awareness Presenter(s): [Shimada] [Golyanik] [Xu] [Perez] [Theobalt]
[SIGGRAPH 2021]
![HodgeNet: learning spectral geometry on triangle meshes](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Smirnov_HodgeNet_-Learning-Spectral-Geometry-on-Triangle-Meshes-150x150.jpg)
HodgeNet: learning spectral geometry on triangle meshes Presenter(s): [Smirnov] [Solomon]
[SIGGRAPH 2021]
![Constrained willmore surfaces](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Soliman_Constrained-Willmore-Surfaces-150x150.jpg)
Constrained willmore surfaces Presenter(s): [Soliman] [Chern] [Diamanti] [Knöppel] [Pinkall] [Schröder]
[SIGGRAPH 2021]
![AgileGAN: stylizing portraits by inversion-consistent transfer learning](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Song_AgileGAN_-Stylizing-Portraits-by-Inversion-Consistent-Transfer-Learning-150x150.jpg)
AgileGAN: stylizing portraits by inversion-consistent transfer learning Presenter(s): [Song] [Luo] [Liu] [Ma] [Lai] [Zheng] [Cham]
[SIGGRAPH 2021]
![Mechanics-aware deformation of yarn pattern geometry](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Sperl_Mechanics-Aware-Deformation-of-Yarn-Pattern-Geometry-150x150.jpg)
Mechanics-aware deformation of yarn pattern geometry Presenter(s): [Sperl] [Narain] [Wojtan]
[SIGGRAPH 2021]
![Learning active quasistatic physics-based models from data](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Grama_Learning-active-quasistatic-physics-based-models-from-data-150x150.jpg)
Learning active quasistatic physics-based models from data Presenter(s): [Srinivasan] [Wang] [Rojas] [Klár] [Kavan] [Sifakis]
[SIGGRAPH 2021]
![Neural animation layering for synthesizing martial arts movements](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Starke_Neural-Animation-Layering-for-Synthesizing-Martial-Arts-Movements-150x150.jpg)
Neural animation layering for synthesizing martial arts movements Presenter(s): [Starke] [Zhao] [Zinno] [Komura]
[SIGGRAPH 2021]
![A unified second-order accurate in time MPM formulation for simulating viscoelastic liquids with phase change](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Su_A-Unified-Second-Order-Accurate-in-Time-MPM-Formulation-for-Simulating-Viscoelastic-Liquids-with-Phase-Change-150x150.jpg)
A unified second-order accurate in time MPM formulation for simulating viscoelastic liquids with phase change Presenter(s): [Su] [Xue] [Han] [Jiang] [Aanjaneya]
[SIGGRAPH 2021]
![End-to-end complex lens design with differentiate ray tracing](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Sun_End-to-End-Complex-Lens-Design-with-Differentiable-Ray-Tracing-150x150.jpg)
End-to-end complex lens design with differentiate ray tracing Presenter(s): [Sun] [Wang] [Fu] [Dun] [Heidrich]
[SIGGRAPH 2021]
![Designing an encoder for StyleGAN image manipulation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Tov_Designing-an-Encoder-for-StyleGAN-Image-Manipulation-150x150.jpg)
Designing an encoder for StyleGAN image manipulation Presenter(s): [Tov] [Alaluf] [Nitzan] [Patashnik] [Cohen-Or]
[SIGGRAPH 2021]
![The shape matching element method: direct animation of curved surface models](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Trusty_High-order-Differentiable-Autoencoder-for-Nonlinear-Model-Reduction-150x150.jpg)
The shape matching element method: direct animation of curved surface models Presenter(s): [Trusty] [Chen] [Levin]
[SIGGRAPH 2021]
![StrokeStrip: joint parameterization and fitting of stroke clusters](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Mossel_StrokeStrip_-Joint-Parameterization-and-Fitting-of-Stroke-Clusters-150x150.jpg)
StrokeStrip: joint parameterization and fitting of stroke clusters Presenter(s): [Van Mossel] [Liu] [Vining] [Bessmeltsev] [Sheffer]
[SIGGRAPH 2021]
![A non-exponential transmittance model for volumetric scene representations](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Vicini_A-Non-Exponential-Transmittance-Model-for-Volumetric-Scene-Representations-150x150.jpg)
A non-exponential transmittance model for volumetric scene representations Presenter(s): [Vicini] [Jakob] [Kaplayan]
[SIGGRAPH 2021]
![Path replay backpropagation: differentiating light paths using constant memory and linear time](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Vicini_Path-Replay-Backpropagation_-Differentiating-Light-Paths-using-Constant-Memory-and-Linear-Time-150x150.jpg)
Path replay backpropagation: differentiating light paths using constant memory and linear time Presenter(s): [Vicini] [Speierer] [Jakob]
[SIGGRAPH 2021]
![Beyond blur: real-time ventral metamers for foveated rendering](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Walton_Beyond-Blur_-Real-time-Ventral-Metamers-for-Foveated-Rendering-150x150.jpg)
Beyond blur: real-time ventral metamers for foveated rendering Presenter(s): [Walton] [Dos Anjos] [Friston] [Swapp] [Akşit] [Steed] [Ritschel]
[SIGGRAPH 2021]
![Fast quasi-harmonic weights for geometric data interpolation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Wang_Fast-Quasi-Harmonic-Weights-for-Geometric-Data-Interpolation-150x150.jpg)
Fast quasi-harmonic weights for geometric data interpolation Presenter(s): [Wang] [Solomon]
[SIGGRAPH 2021]
![MOCCA: modeling and optimizing cone-joints for complex assemblies](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Wang_MOCCA-Modeling-and-Optimizing-Cone-joints-for-Complex-Assemblies-150x150.jpg)
MOCCA: modeling and optimizing cone-joints for complex assemblies Presenter(s): [Wang] [Song] [Pauly]
[SIGGRAPH 2021]
![Thin-film smoothed particle hydrodynamics fluid](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Wang_Thin-Film-Smoothed-Particle-Hydrodynamics-Fluid-150x150.jpg)
Thin-film smoothed particle hydrodynamics fluid Presenter(s): [Wang] [Deng] [Kong] [Prasad] [Xiong] [Zhu]
[SIGGRAPH 2021]
![Tracing versus freehand for evaluating computer-generated drawings](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Wang_Tracing-Versus-Freehand-for-Evaluating-Computer-Generated-Drawings-150x150.jpg)
Tracing versus freehand for evaluating computer-generated drawings Presenter(s): [Wang] [Qju] [Feng] [Rushmeier] [McMillan] [Dorsey]
[SIGGRAPH 2021]
![A fitted radiance and attenuation model for realistic atmospheres](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Wilkie_A-Fitted-Radiance-and-Attenuation-Model-for-Realistic-Atmospheres-150x150.jpg)
A fitted radiance and attenuation model for realistic atmospheres Presenter(s): [Wilkie] [Vévoda] [Bashford-Rogers] [Hosek] [Iser] [Kolářová] [Rittig] [Křivánek]
[SIGGRAPH 2021]
![Fusion 360 gallery: a dataset and environment for programmatic CAD construction from human design sequences](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Willis_Fusion-360-Gallery_-A-Dataset-and-Environment-for-Programmatic-CAD-Construction-from-Human-Design-Sequences-150x150.jpg)
Fusion 360 gallery: a dataset and environment for programmatic CAD construction from human design sequences Presenter(s): [Willis] [Pu] [Luo] [Chu] [Du] [Lambourne] [Solar-Lezama] [Matusik]
[SIGGRAPH 2021]
![Control strategies for physically simulated characters performing two-player competitive sports](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Won_Control-Strategies-for-Physically-Simulated-Characters-Performing-Two-player-Competitive-Sports-150x150.jpg)
Control strategies for physically simulated characters performing two-player competitive sports Presenter(s): [Won] [Gopinath] [Hodgins]
[SIGGRAPH 2021]
![Coarse-to-fine: facial structure editing of portrait images via latent space classifications](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Wu_Coarse-to-Fine-Facial-Structure-Editing-of-Portrait-Images-via-Latent-Space-Classifications-150x150.jpg)
Coarse-to-fine: facial structure editing of portrait images via latent space classifications Presenter(s): [Wu] [Yang] [Xiao] [Jin]
[SIGGRAPH 2021]
![Eliminating topological errors in neural network rotation estimation using self-selecting ensembles](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Xiang_Eliminating-Topological-Errors-in-Neural-Network-Rotation-Estimation-Using-Self-selecting-Ensembles-150x150.jpg)
Eliminating topological errors in neural network rotation estimation using self-selecting ensembles Presenter(s): [Xiang]
[SIGGRAPH 2021]
![Seamless manga inpainting with semantics awareness](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Xie_Seamless-Manga-Inpainting-with-Semantics-Awareness-150x150.jpg)
Seamless manga inpainting with semantics awareness Presenter(s): [Xie] [Xia] [Li] [Wong]
[SIGGRAPH 2021]
![Incompressible flow simulation on vortex segment clouds](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Xiong_Incompressible-Flow-Simulation-on-Vortex-Segment-Clouds-150x150.jpg)
Incompressible flow simulation on vortex segment clouds Presenter(s): [Xiong] [Tao] [Zhang] [Feng] [Zhu]
[SIGGRAPH 2021]
![Scalable image-based indoor scene rendering with reflections](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Xu_Scalable-Image-based-Indoor-Scene-Rendering-with-Reflections-150x150.jpg)
Scalable image-based indoor scene rendering with reflections Presenter(s): [Xu] [Wu] [Zu] [Huang] [Yang] [Bao] [Xu]
[SIGGRAPH 2021]
![DeepFormableTag: end-to-end generation and recognition of deformable fiducial markers](https://history.siggraph.org/wp-content/uploads/2022/05/SIGGRAPH2021_Image-Not-Available-150x150.jpg)
DeepFormableTag: end-to-end generation and recognition of deformable fiducial markers Presenter(s): [Yaldiz] [Meuleman] [Jang] [Ha] [Kim]
[SIGGRAPH 2021]
![Unsupervised learning for cuboid shape abstraction via joint segmentation from point clouds](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Yang_Unsupervised-Learning-for-Cuboid-Shape-Abstraction-via-Joint-Segmentation-from-Point-Clouds-150x150.jpg)
Unsupervised learning for cuboid shape abstraction via joint segmentation from point clouds Presenter(s): [Yang] [Chen]
[SIGGRAPH 2021]
![WireRoom: model-guided explorative design of abstract wire art](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Yang_WireRoom-Model-guided-Explorative-Design-of-Abstract-Wire-Art-150x150.jpg)
WireRoom: model-guided explorative design of abstract wire art Presenter(s): [Yang] [Xu] [Fu] [Huang]
[SIGGRAPH 2021]
![TransPose: real-time 3D human translation and pose estimation with six inertial sensors](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Yi_TransPose-Real-time-3D-Human-Translation-and-Pose-Estimation-with-Six-Inertial-Sensors-150x150.jpg)
TransPose: real-time 3D human translation and pose estimation with six inertial sensors Presenter(s): [Yi] [Zhou] [Xu]
[SIGGRAPH 2021]
![Discovering diverse athletic jumping strategies](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Yin_Discovering-Diverse-Athletic-Jumping-Strategies-150x150.jpg)
Discovering diverse athletic jumping strategies Presenter(s): [Yin] [Yang] [Panne] [Yin]
[SIGGRAPH 2021]
![Monte Carlo estimators for differential light transport](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Zeltner_Monte-Carlo-Estimators-for-Differential-Light-Transport-150x150.jpg)
Monte Carlo estimators for differential light transport Presenter(s): [Zeltner] [Speierer] [Georgiev] [Jakob]
[SIGGRAPH 2021]
![Antithetic sampling for Monte Carlo differentiable rendering](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Zhang_Antithetic-Sampling-for-Monte-Carlo-Differentiable-Rendering-150x150.jpg)
Antithetic sampling for Monte Carlo differentiable rendering Presenter(s): [Zhang] [Dong] [Doggett] [Zhao]
[SIGGRAPH 2021]
![Consistent depth of moving objects in video](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Zhang_Consistent-Depth-of-Moving-Objects-in-Video-150x150.jpg)
Consistent depth of moving objects in video Presenter(s): [Zhang] [Cole] [Tucker] [Freeman] [Dekel]
[SIGGRAPH 2021]
![Editable free-viewpoint video using a layered neural representation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Zhang_Editable-Free-Viewpoint-Video-using-a-Layered-Neural-Representation-150x150.jpg)
Editable free-viewpoint video using a layered neural representation Presenter(s): [Zhang] [Liu] [Ye] [Zhao] [Zhang] [Wu] [Zhang] [Yu] [Xu]
[SIGGRAPH 2021]
![Learning skeletal articulations with neural blend shapes](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Li_Learning-Skeletal-Articulations-with-Neural-Blend-Shapes-150x150.jpg)
Learning skeletal articulations with neural blend shapes Presenter(s): [Zhang] [Aberman] [Hanocka] [Liu] [Sorkine-Hornung] [Chen]
[SIGGRAPH 2021]
![ManipNet: neural manipulation synthesis with a hand-object spatial representation](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Zhang_ManipNet-Neural-Manipulation-Synthesis-with-a-Hand-Object-Spatial-Representation-150x150.jpg)
ManipNet: neural manipulation synthesis with a hand-object spatial representation Presenter(s): [Zhang] [Ye] [Shiratori] [Komura]
[SIGGRAPH 2021]
![Path-space differentiable rendering of participating media](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Zhang_Path-Space-Differentiable-Rendering-of-Participating-Media-150x150.jpg)
Path-space differentiable rendering of participating media Presenter(s): [Zhang] [Yu] [Zhao]
[SIGGRAPH 2021]
![ROSEFusion: random optimization for online dense reconstruction under fast camera motion](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Zhang_ROSEFusion-Random-Optimization-for-Online-Dense-Reconstruction-under-Fast-Camera-Motion-150x150.jpg)
ROSEFusion: random optimization for online dense reconstruction under fast camera motion Presenter(s): [Zhang] [Zhu] [Zheng] [Xu]
[SIGGRAPH 2021]