EDGE: Editable Dance Generation from Music
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About
EDGE is a state-of-the-art tool for editable dance generation that creates realistic, physically plausible dance movements while matching the characteristics of input music. Utilizing a transformer-based diffusion model paired with the Jukebox music feature extractor, EDGE allows for powerful editing capabilities such as joint-wise conditioning, motion in-betweening, and dance continuation. It effectively generates choreographies from a variety of music styles and can create dance sequences of any length by enforcing temporal constraints. The tool is trained to ensure physical realism, avoiding common issues like sliding feet during dance movements. Human evaluations show a strong preference for dances generated by EDGE over those produced by existing methods.
Platform
Task
Features
• motion in-betweening
• dance continuation
• joint-wise conditioning
• contact consistency loss
• physical realism
• generates arbitrary-length dances
• music-based choreography
• editable dance generation
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