Taku Komura
Most Recent Affiliation(s):
- University of Edinburgh
Other / Past Affiliation(s):
- The University of Hong Kong
Learning Category: Jury Member:
Experience(s):
Learning Category: Presentation(s):
![Bodyformer: Semantics-guided 3D Body Gesture Synthesis With Transformer](https://history.siggraph.org/wp-content/uploads/2024/02/2023-Tech-Papers-Pang_Semantics-guided-3D-Body-Gesture-Synthesis-with-Transformer-150x150.jpg)
Type: [Technical Papers]
Bodyformer: Semantics-guided 3D Body Gesture Synthesis With Transformer Presenter(s): [Pang] [Qin] [Fan] [Habekost] [Shiratori] [Yamagishi] [Komura]
[SIGGRAPH 2023]
![NeRO: Neural Geometry and BRDF Reconstruction of Reflective Objects From Multiview Images](https://history.siggraph.org/wp-content/uploads/2024/02/2023-Tech-Papers-Liu_NeRO-Neural-Geometry-and-BRDF-Reconstruction-of-Reflective-Objects-from-Multiview-Images-150x150.jpg)
Type: [Technical Papers]
NeRO: Neural Geometry and BRDF Reconstruction of Reflective Objects From Multiview Images Presenter(s): [Liu] [Wang] [Lin] [Long] [Wang] [Liu] [Komura] [Wang]
[SIGGRAPH 2023]
![Neural Face Rigging for Animating and Retargeting Facial Meshes in the Wild](https://history.siggraph.org/wp-content/uploads/2024/02/2023-Tech-Papers-Qin_Neural-Face-Rigging-for-Animating-and-Retargeting-Faces-in-the-Wild-150x150.jpg)
Type: [Technical Papers]
Neural Face Rigging for Animating and Retargeting Facial Meshes in the Wild Presenter(s): [Qin] [Saito] [Aigerman] [Groueix] [Komura]
[SIGGRAPH 2023]
![DeepPhase: periodic autoencoders for learning motion phase manifolds](https://history.siggraph.org/wp-content/uploads/2023/06/2022-Technical-Papers-Starke_-DeepPhase-Periodic-Autoencoders-for-Learning-Motion-Phase-Manifolds-150x150.jpg)
Type: [Technical Papers]
DeepPhase: periodic autoencoders for learning motion phase manifolds Presenter(s): [Starke] [Mason] [Komura]
[SIGGRAPH 2022]
![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)
Type: [Technical Papers]
ManipNet: neural manipulation synthesis with a hand-object spatial representation Presenter(s): [Zhang] [Ye] [Shiratori] [Komura]
[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)
Type: [Technical Papers]
Neural animation layering for synthesizing martial arts movements Presenter(s): [Starke] [Zhao] [Zinno] [Komura]
[SIGGRAPH 2021]
![Local Motion Phases for Learning Multi-Contact Character Movements](https://history.siggraph.org/wp-content/uploads/2022/09/2020-Technical-Papers-Starke_Local-Motion-Phases-for-Learning-Multi-Contact-Character-Movements-150x150.jpg)
Type: [Technical Papers]
Local Motion Phases for Learning Multi-Contact Character Movements Presenter(s): [Starke] [Zhao] [Komura] [Zaman]
[SIGGRAPH 2020]
![Mode-adaptive neural networks for quadruped motion control](https://history.siggraph.org/wp-content/uploads/2023/02/2018-Technical-Papers-Zhang_Mode-Adaptive-Neural-Networks-for-Quadruped-Motion-Control-150x150.jpg)
Type: [Technical Papers]
Mode-adaptive neural networks for quadruped motion control Presenter(s): [Zhang] [Starke] [Komura] [Saito]
Entry No.: [145]
[SIGGRAPH 2018]
![Phase-functioned neural networks for character control](https://history.siggraph.org/wp-content/uploads/2023/02/2017-Technical-Papers-Holden_Phase-Functioned-Neural-Networks-for-Character-Control-150x150.jpg)
Type: [Technical Papers]
Phase-functioned neural networks for character control Presenter(s): [Holden] [Komura] [Saito]
[SIGGRAPH 2017]
![A deep learning framework for character motion synthesis and editing](https://history.siggraph.org/wp-content/uploads/2023/02/2016-Technical-Papers-Holden_A-Deep-Learning-Framework-for-Character-Motion-Synthesis-and-Editing-150x150.jpg)
Type: [Technical Papers]
A deep learning framework for character motion synthesis and editing Presenter(s): [Holden] [Saito] [Komura]
[SIGGRAPH 2016]
![Harmonic Parameterization by Electrostatics](https://history.siggraph.org/wp-content/uploads/2022/07/2014-SIGGRAPH-Image-Not-Available-150x150.jpg)
Type: [Technical Papers]
Harmonic Parameterization by Electrostatics Presenter(s): [Wang] [Sidorov] [Sandilands] [Komura]
[SIGGRAPH 2014]
![Indexing 3D Scenes Using the Interaction Bisector Surface](https://history.siggraph.org/wp-content/uploads/2022/07/2014-SIGGRAPH-Image-Not-Available-150x150.jpg)
Type: [Technical Papers]
Indexing 3D Scenes Using the Interaction Bisector Surface Presenter(s): [Zhao] [Wang] [Komura]
[SIGGRAPH 2014]
![Spatial relationship preserving character motion adaptation](https://history.siggraph.org/wp-content/uploads/2023/03/2010-Technical-Papers-Ho_Dynamic-Local-Remeshing-for-Elastoplastic-Simulation-150x150.jpg)
Type: [Technical Papers]
Spatial relationship preserving character motion adaptation Presenter(s): [Ho] [Komura] [Tai]
[SIGGRAPH 2010]
Role(s):
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