Exploring Multi-Modal Control in Music-Driven Dance Generation
Ronghui Li Yuqin Dai Yachao Zhang Jun Li Jian Yang Jie Guo Xiu Li
Existing music-driven 3D dance generation methods mainly concentrate on
high-quality dance generation, but lack sufficient control during the
generation process. To address these issues, we propose a unified framework
capable of generating high-quality dance movements and supporting multi-modal
control, including genre control, semantic control, and spatial control. First,
we decouple the dance generation network from the dance control network,
thereby avoiding the degradation in dance quality when adding additional
control information. Second, we design specific control strategies for
different control information and integrate them into a unified framework.
Experimental results show that the proposed dance generation framework
outperforms state-of-the-art methods in terms of motion quality and
controllability.