Xuebin (Jason) Peng
Most Recent Affiliation(s):
- University of California
Award(s):
Learning Presentation(s):
![CALM: Conditional Adversarial Latent Models for Directable Virtual Characters](https://history.siggraph.org/wp-content/uploads/2024/02/2023-Tech-Papers-Tessler_CALM-Conditional-Adversarial-Latent-Models-for-Directable-Virtual-Characters-150x150.jpg)
Type: [Technical Papers]
CALM: Conditional Adversarial Latent Models for Directable Virtual Characters Presenter(s): [Tessler] [Guo] [Mannor] [Chechik] [Peng]
[SIGGRAPH 2023]
![Learning Physically Simulated Tennis Skills from Broadcast Videos](https://history.siggraph.org/wp-content/uploads/2024/02/2023-Tech-Papers-Zhang_Learning-Physically-Simulated-Tennis-Skills-from-Broadcast-Videos-02-150x150.jpg)
Type: [Technical Papers]
Learning Physically Simulated Tennis Skills from Broadcast Videos Presenter(s): [Zhang] [Makoviychuk] [Yuan] [Guo] [Fidler] [Peng] [Fatahalian]
[SIGGRAPH 2023]
![Synthesizing Physical Character-Scene Interactions](https://history.siggraph.org/wp-content/uploads/2024/02/2023-Tech-Papers-Hassan_Synthesizing-Physical-Character-Scene-Interactions-02-150x150.jpg)
Type: [Technical Papers]
Synthesizing Physical Character-Scene Interactions Presenter(s): [Hassan] [Guo] [Wang] [Black] [Fidler] [Peng]
[SIGGRAPH 2023]
![ASE: large-scale reusable adversarial skill embeddings for physically simulated characters](https://history.siggraph.org/wp-content/uploads/2023/10/2022-Technical-Paper-Peng_ASE-Large-scale-Reusable-Adversarial-Skill-Embeddings-for-Physically-Simulated-Characters-150x150.jpg)
Type: [Technical Papers]
ASE: large-scale reusable adversarial skill embeddings for physically simulated characters Presenter(s): [Peng] [Guo] [Halper] [Levine] [Fidler]
[SIGGRAPH 2022]
![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)
Type: [Technical Papers]
AMP: adversarial motion priors for stylized physics-based character control Presenter(s): [Peng] [Ma] [Abbeel] [Levine] [Kanazawa]
[SIGGRAPH 2021]
![DeepMimic: example-guided deep reinforcement learning of physics-based character skills](https://history.siggraph.org/wp-content/uploads/2023/02/2018-Technical-Papers-Peng_DeepMimic_-Example-Guided-Deep-Reinforcement-Learning-of-Physics-Based-Character-Skills-150x150.jpg)
Type: [Technical Papers]
DeepMimic: example-guided deep reinforcement learning of physics-based character skills Presenter(s): [Peng] [Abbeel] [Levine] [Panne]
Entry No.: [143]
[SIGGRAPH 2018]
![DeepLoco: dynamic locomotion skills using hierarchical deep reinforcement learning](https://history.siggraph.org/wp-content/uploads/2023/02/2017-Technical-Papers-Peng_DeepLoco_-Dynamic-Locomotion-Skills-Using-Hierarchical-Deep-Reinforcement-Learning-150x150.jpg)
Type: [Technical Papers]
DeepLoco: dynamic locomotion skills using hierarchical deep reinforcement learning Presenter(s): [Peng] [Berseth] [Yin] [Panne]
[SIGGRAPH 2017]
Role(s):
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