82 citations · 86 across the 3 of their papers we have counts for
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cs.GR2022★ 82 cited
ControlVAE: Model-Based Learning of Generative Controllers for Physics-Based Characters
Heyuan Yao, Zhenhua Song, Baoquan Chen +1
In this paper, we introduce ControlVAE, a novel model-based framework for learning generative motion control policies based on variational autoencoders (VAE). Our framework can lea…
cs.GR2022★ 1 cited
Neural3Points: Learning to Generate Physically Realistic Full-body Motion for Virtual Reality Users
Yongjing Ye, Libin Liu, Lei Hu +1
Animating an avatar that reflects a user's action in the VR world enables natural interactions with the virtual environment. It has the potential to allow remote users to communica…
cs.GR2021
Learning Skeletal Articulations with Neural Blend Shapes
Peizhuo Li, Kfir Aberman, Rana Hanocka +3
Animating a newly designed character using motion capture (mocap) data is a long standing problem in computer animation. A key consideration is the skeletal structure that should c…