What is it about?

Reproducing human behaviors in a realistic way is a fundamental research goal in computer animation research. In this work, we present a way of producing human motions in a physically believable manner by using physically simulated characters, conditional VAEs, and reinforcement learning.

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Why is it important?

Learning controllers for physically simulated characters is very time-consuming and computationally expensive. Training a backbone model that can be reused for many different downstream tasks is a promising way of resolving those problems. We introduce a new way of training a backbone model for physically simulated characters and demonstrate that many challenging downstream tasks can efficiently be solved by using our model.


I hope the method will be a stepping stone to build a general purpose backbone model that can handle large and diverse behaviors. I hope this article inspires not only researchers in computer graphics but also researchers in other domains such as robotics and machine learning.

Jungdam Won
Facebook Inc

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This page is a summary of: Physics-based character controllers using conditional VAEs, ACM Transactions on Graphics, July 2022, ACM (Association for Computing Machinery), DOI: 10.1145/3528223.3530067.
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