Harmonious Group Choreography with Trajectory-Controllable Diffusion
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , , , , , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2024
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866910815741804544 |
|---|---|
| author | Dai, Yuqin Zhu, Wanlu Li, Ronghui Ren, Zeping Zhou, Xiangzheng Ying, Jixuan Li, Jun Yang, Jian |
| author_facet | Dai, Yuqin Zhu, Wanlu Li, Ronghui Ren, Zeping Zhou, Xiangzheng Ying, Jixuan Li, Jun Yang, Jian |
| contents | Creating group choreography from music is crucial in cultural entertainment and virtual reality, with a focus on generating harmonious movements. Despite growing interest, recent approaches often struggle with two major challenges: multi-dancer collisions and single-dancer foot sliding. To address these challenges, we propose a Trajectory-Controllable Diffusion (TCDiff) framework, which leverages non-overlapping trajectories to ensure coherent and aesthetically pleasing dance movements. To mitigate collisions, we introduce a Dance-Trajectory Navigator that generates collision-free trajectories for multiple dancers, utilizing a distance-consistency loss to maintain optimal spacing. Furthermore, to reduce foot sliding, we present a footwork adaptor that adjusts trajectory displacement between frames, supported by a relative forward-kinematic loss to further reinforce the correlation between movements and trajectories. Experiments demonstrate our method's superiority. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_06189 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Harmonious Group Choreography with Trajectory-Controllable Diffusion Dai, Yuqin Zhu, Wanlu Li, Ronghui Ren, Zeping Zhou, Xiangzheng Ying, Jixuan Li, Jun Yang, Jian Computer Vision and Pattern Recognition Creating group choreography from music is crucial in cultural entertainment and virtual reality, with a focus on generating harmonious movements. Despite growing interest, recent approaches often struggle with two major challenges: multi-dancer collisions and single-dancer foot sliding. To address these challenges, we propose a Trajectory-Controllable Diffusion (TCDiff) framework, which leverages non-overlapping trajectories to ensure coherent and aesthetically pleasing dance movements. To mitigate collisions, we introduce a Dance-Trajectory Navigator that generates collision-free trajectories for multiple dancers, utilizing a distance-consistency loss to maintain optimal spacing. Furthermore, to reduce foot sliding, we present a footwork adaptor that adjusts trajectory displacement between frames, supported by a relative forward-kinematic loss to further reinforce the correlation between movements and trajectories. Experiments demonstrate our method's superiority. |
| title | Harmonious Group Choreography with Trajectory-Controllable Diffusion |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2403.06189 |