CoDancers: Music-Driven Coherent Group Dance Generation with Choreographic Unit

Dance and music are intimately interconnected, with group dance being a crucial part of dance artistry. Consequently, Music-Driven Group Dance Generation has been a fundamental and challenging task in various fields like education, art, and sports. However, existing methods fail to fully explore group dance coherence. Thus, we propose CoDancers, a novel and efficient retrieval-based music-driven group dance generation framework. CoDancers improves performance by decomposing group dance coherence into individual movement coherence and group interaction coherence for specialized design, incorporating a Spatial-Temporal Group Dance Blender block, a Acoustic-Semantic Music Miner block, and a Stereotype-Reducing Dance Generator block. Experimental results on the public dataset demonstrate the superiority of our method over existing baselines, achieving state-of-the-art performance. The code is available at https://github.com/XulongT/CoDancers.