ChoreoMaster: choreography-oriented music-driven dance synthesis
Kang Chen, Zhipeng Tan, Jin Lei, Song-Hai Zhang, Yuan-Chen Guo, Weidong Zhang, Shi-Min Hu
Abstract
Despite strong demand in the game and film industry, automatically synthesizing high-quality dance motions remains a challenging task. In this paper, we present ChoreoMaster, a production-ready music-driven dance motion synthesis system. Given a piece of music, ChoreoMaster can automatically generate a high-quality dance motion sequence to accompany the input music in terms of style, rhythm and structure. To achieve this goal, we introduce a novel choreography-oriented choreomusical embedding framework, which successfully constructs a unified choreomusical embedding space for both style and rhythm relationships between music and dance phrases. The learned choreomusical embedding is then incorporated into a novel choreography-oriented graph-based motion synthesis framework, which can robustly and efficiently generate high-quality dance motions following various choreographic rules. Moreover, as a production-ready system, ChoreoMaster is sufficiently controllable and comprehensive for users to produce desired results. Experimental results demonstrate that dance motions generated by ChoreoMaster are accepted by professional artists.
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Cited by top-tier papers35
- AI Choreographer: Music Conditioned 3D Dance Generation with AIST++Ruilong Li, Shan Yang, David A. Ross, Angjoo KanazawaICCV 2021 · 701 citations
- Listen, Denoise, Action! Audio-Driven Motion Synthesis with Diffusion ModelsSimon Alexanderson, Rajmund Nagy, Jonas Beskow, Gustav Eje HenterSIGGRAPH 2023 · 191 citations
- DanceFormer: Music Conditioned 3D Dance Generation with Parametric Motion TransformerBuyu Li, Yongchi Zhao, Zhelun Shi, Lu ShengAAAI 2022 · 182 citations
- FineDance: A Fine-grained Choreography Dataset for 3D Full Body Dance GenerationRonghui Li, Junfan Zhao, Yachao Zhang, Mingyang Su et al.ICCV 2023 · 110 citations
- TM2D: Bimodality Driven 3D Dance Generation via Music-Text IntegrationKehong Gong, Dongze Lian, Heng Chang, Chuan Guo et al.ICCV 2023 · 103 citations
Builds on3
- Convolutional Sequence Generation for Skeleton-Based Action SynthesisSijie Yan, Zhizhong Li, Yuanjun Xiong, Huahan Yan et al.ICCV 2019 · 169 citations
- Self-supervised Dance Video Synthesis Conditioned on MusicXuanchi Ren, Haoran Li, Zijian Huang, Qifeng ChenACM MM 2020 · 68 citations
- ChoreoNet: Towards Music to Dance Synthesis with Choreographic Action UnitZijie Ye, Haozhe Wu, Jia Jia, Yaohua Bu et al.ACM MM 2020 · 59 citations
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