Breaking the Group Size Barrier: Parameter-Efficient Group Dance Generation with Chain-of-Dancers
Group dance generation aims to synthesize coordinated multi-dancer choreography from music, with broad applications in animation and interactive content creation. This task requires modeling dense inter-person dependencies to ensure spatial coordination, while naturally preserving individual dancer identities. Existing approaches model all dancers jointly with end-to-end transformers, which tie the architecture to a fixed group size and entangle per-dancer identities across frames. We propose ChainDance, a scalable framework that reformulates group dance generation as a Chain-of-Dancers: a sequential decomposition over per-dancer conditional distributions, allowing a single model to scale...
| Authors | Jing Xu, Cunjian Chen, Qiuhong Ke |
|---|---|
| Primary category | cs.CV |
| Published | 8 October 2026 |
| Last updated at source | 8 October 2026 |
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