title: A Music-Driven Dance Generation Method Based on a Spatial-Temporal Refinement Model to Optimize Abnormal Frames
abstract: Since existing music-driven dance generation methods have abnormal motion when generating dance sequences which leads to unnatural overall dance movements, a music-driven dance generation method based on a spatial-temporal refinement model is proposed to optimize the abnormal frames. Firstly, the cross-modal alignment model is used to learn the correspondence between the two modalities of audio and dance video and based on the learned correspondence, the corresponding dance segments are matched 
journal: Sensors