GAIL

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 …

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 …