BiTDiff: Fine-Grained 3D Conducting Motion Generation via BiMamba-Transformer Diffusion
3D conducting motion generation aims to synthesize fine-grained conductor motions from music, with broad potential in music education, virtual performance, digital human animation, and human-AI co-creation. However, this task remains underexplored due to two major challenges: (1) the lack of large-scale fine-grained 3D conducting datasets and (2) the absence of effective methods that can jointly support long-sequence generation with high quality and efficiency. To address the data limitation, we develop a quality-oriented 3D conducting motion collection pipeline and construct CM-Data, a fine-grained SMPL-X dataset with about 10 hours of conducting motion data. To the best of our knowledge...
| Authors | Tianzhi Jia, Kaixing Yang, Xiaole Yang et al. |
|---|---|
| Primary category | cs.CV |
| Published | 6 April 2026 |
| Last updated at source | 23 April 2026 |
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