DanceDuo: Bridging Human Movement and AI Choreography
In recent years, advancements in deep learning and generative models have revolutionized music-driven dance generation. This paper introduces a novel platform, namely DanceDuo, leveraging diffusion models to generate AI-choreographed dance sequences synchronized with a variety of music genres, to encourage dancing practice. The system allows users to interact with AI by selecting music tracks, humanoid models, and importing personal dance videos for comparison, fostering a rich and engaging user experience. DanceDuo not only offers dance generation but also integrates human pose estimation models to provide users with insightful comparisons of their own performances with AI-generated sequ...
| Authors | Gia-Cat Bui-Le, Tuong-Vy Truong-Thuy, Hai-Dang Nguyen et al. |
|---|---|
| Primary category | cs.HC |
| Published | 25 June 2026 |
| Last updated at source | 25 June 2026 |
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