Presentation

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MoConVQ: Unified Physics-based Motion Control via Scalable Discrete Representations

DescriptionWe present MoConVQ, a uniform framework enabling simulated avatars to acquire diverse skills from large, unstructured datasets. Leveraging a rich and scalable discrete skill representation, MoConVQ supports a broad range of applications, including pose estimation, interactive control, text-to-motion generation, and, more interestingly, integrating motion generation with Large Language Models (LLMs).

Authors

Heyuan Yao

School of Computer Science, Peking University

Zhenhua Song

School of Computer Science, Peking University

Yuyang Zhou

Peking University, School of EECS

Tenglong Ao

School of Computer Science, Peking University