Page 181 – ACM SIGGRAPH HISTORY ARCHIVES
2019 SA Technical Papers_Nakada_Biomimetic eye modeling & deep neuromuscular oculomotor control

“Biomimetic eye modeling & deep neuromuscular oculomotor control” by Nakada, Lakshmipathy, Chen, Ling, Zhou, et al. …

2009 SA Technical Paper: Skipping Steps in Deformable Simulation with Online Model Reduction

“Skipping steps in deformable simulation with online model reduction” by Kim and James

2019 SA Technical Papers_Wang_Learning an intrinsic garment space for interactive authoring of garment animation

“Learning an intrinsic garment space for interactive authoring of garment animation” by Wang, Shao, Fu and Mitra

2019 SA Technical Papers_Zou_Language-based colorization of scene sketches

“Language-based colorization of scene sketches” by Zou, Mo, Gao, Du and Fu

2019 SA Technical Papers_Gryaditskaya_OpenSketch: a richly-annotated dataset of product design sketches

“OpenSketch: a richly-annotated dataset of product design sketches” by Gryaditskaya, Sypesteyn, Hoftijzer, Pont, Durand, et al. …

2019 SA Technical Papers_Hladky_The camera offset space: real-time potentially visible set computations for streaming rendering

“The camera offset space: real-time potentially visible set computations for streaming rendering” by Hladky, Seidel and Steinberger

2019 SA Technical Papers_Yifan_Differentiable surface splatting for point-based geometry processing

“Differentiable surface splatting for point-based geometry processing” by Wang, Serena, Wu, Öztireli and Sorkine-Hornung

2019 SA Technical Papers_Seyb_Non-linear sphere tracing for rendering deformed signed distance fields

“Non-linear sphere tracing for rendering deformed signed distance fields” by Seyb, Jacobson, Nowrouzezahrai and Jarosz

2019 SA Technical Papers_Loubet_Reparameterizing discontinuous integrands for differentiable rendering

“Reparameterizing discontinuous integrands for differentiable rendering” by Loubet, Holzschuch and Jakob

2019 SA Technical Papers_Zhang_A differential theory of radiative transfer

“A differential theory of radiative transfer” by Zhang, Wu, Zheng, Gkioulekas, Ramamoorthi, et al. …

2019 SA Technical Papers_ Leimkühler_Deep point correlation design

“Deep point correlation design” by Leimkühler, Singh, Myszkowski, Seidel and Ritschel

2019 SA Technical Papers_Hahn_Real2Sim: visco-elastic parameter estimation from dynamic motion

“Real2Sim: visco-elastic parameter estimation from dynamic motion” by Hahn, Banzet, Bern and Coros

2019 SA Technical Papers_Eckert_ScalarFlow: a large-scale volumetric data set of real-world scalar transport flows for computer animation and machine learning

“ScalarFlow: a large-scale volumetric data set of real-world scalar transport flows for computer animation and machine learning” by Eckert, Um and Thuerey

2019 SA Technical Papers_Takahashi_Video-guided real-to-virtual parameter transfer for viscous fluids

“Video-guided real-to-virtual parameter transfer for viscous fluids” by Takahashi and Lin

2019 SA Technical Papers_Flynn_Fluid carving: intelligent resizing for fluid simulation data

“Fluid carving: intelligent resizing for fluid simulation data” by Flynn, Egbert, Holladay and Morse

2019 SA Technical Papers_Wu_Data-driven interior plan generation for residential buildings

“Data-driven interior plan generation for residential buildings” by Wu, Fu, Tang, Wang, Qi, et al. …

2019 SA Technical Papers_Yan_RPM-Net: recurrent prediction of motion and parts from point cloud

“RPM-Net: recurrent prediction of motion and parts from point cloud” by Yan, Hu, Yan, Chen, Kaick, et al. …

2019 SA Technical Papers_Sun_Learning adaptive hierarchical cuboid abstractions of 3D shape collections

“Learning adaptive hierarchical cuboid abstractions of 3D shape collections” by Sun, Zou, Tong and Liu

2019 SA Technical Papers_Yang_Dynamic hair modeling from monocular videos using deep neural networks

“Dynamic hair modeling from monocular videos using deep neural networks” by Yang, Shi, Zheng and Zhou

2019 SA Technical Papers_Mo_StructureNet: hierarchical graph networks for 3D shape generation

“StructureNet: hierarchical graph networks for 3D shape generation” by Mo, Guerrero, Yi, Su, Wonka, et al. …

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