TokenDance: Token-to-Token Music-to-Dance Generation with Bidirectional Mamba
Music-to-dance generation has broad applications in virtual reality, dance education, and digital character animation. However, the limited coverage of existing 3D dance datasets confines current models to a narrow subset of music styles and choreographic patterns, resulting in poor generalization to real-world music. Consequently, generated dances often become overly simplistic and repetitive, substantially degrading expressiveness and realism. To tackle this problem, we present TokenDance, a two-stage music-to-dance generation framework that explicitly addresses this limitation through dual-modality tokenization and efficient token-level generation. In the first stage, we discretize bot...
| Authors | Ziyue Yang, Kaixing Yang, Xulong Tang |
|---|---|
| Primary category | cs.AI |
| Published | 28 March 2026 |
| Last updated at source | 28 March 2026 |
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