Home
People
Publications
Teaching
Contact
Light
Dark
Automatic
RL
CBIL: Collective Behavior Imitation Learning for Fish from Real Videos
Reproducing realistic collective behaviors presents a captivating yet formidable challenge. Traditional rule-based methods rely on hand-crafted principles, limiting motion diversity and realism in generated collective behaviors. Recent imitation …
C·ASE: Learning Conditional Adversarial Skill Embeddings for Physics-based Characters
We present C·ASE, an efficient and effective framework that learns Conditional Adversarial Skill Embeddings for physics-based characters. C·ASE enables the physically simulated character to learn a diverse repertoire of skills while providing …
Cite
×