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ChoreoStudio plans music driven group dance formations and moves

ChoreoStudio: Planning What, When, and Who in Music-Driven Group Choreography

Abstract: Music-driven group dance generation must decide not only how each dancer moves, but also what formation the group should form, when it should change, and who should execute each transition. Existing methods can generate orderly and rhythmically synchronized group motion, but remain limited in formation evolution and inter-dancer interaction. In human choreography, formation transitions often align with changes in high-level musical structure, such as the progression from an introduction to a chorus or from a chorus to a climax. We present ChoreoStudio, which makes choreography planning explicit. A music disentangler first decomposes the audio into frame-level rhythmic features and segment-level structural features. Given the segment-level features and sparse labels, a frozen omni-modal model acts as a scriptwriter, producing a global semantic description that guides the Director's choreography planning. Based on this context, the Director produces three coupled interaction decisions: a centroid-relative point set specifies what formation to produce, a transition gate determines when it should change, and a mobility allocation indicates who should execute the transition. The transition gate and mobility allocation are further conditioned on the planned geometric change, coupling formation targets with their temporal and dancer-specific execution. At a finer temporal scale, frame-aligned music features condition the diffusion generator to control detailed body motion and preserve beat-level alignment. The segment-level interaction plan is injected in parallel through frame-aligned instruction tokens and cross-dancer attention biases, coordinating how the generator realizes each transition. Experiments on AIOZ-GDance demonstrate that ChoreoStudio follows the planned interactions while achieving state-of-the-art performance in motion quality, group organization, and formation dynamics.

Fri 23 OctSoundArtificial IntelligenceComputer Vision and Pattern Recognition
The gist
Creating group dances that fit music is tricky because you have to decide how dancers move, what shapes they make, when those shapes change, and who leads each change. The authors show a system called ChoreoStudio that breaks down music into parts and plans the dance based on these structures. It decides dance formations, when to switch them, and which dancers move, all linked to the music’s segments. Their system then turns this plan into detailed synchronized dance moves, improving both the look and timing of group dances.
Open → 2610.32325v1