Music Information Retrieval
This paper presents Diffusion-Conductor , a novel DDIM-based approach for music-driven conducting motion generation, which integrates the diffusion model to a two-stage learning framework. [arxiv]
This paper proposed the first deep-learning based music-driven conducting motion generation method, and presented a large-scale music motion dataset ConductorMotion100 with unprecedented 100 hours length. The associated demo paper won the Best Demo Award in IEEE ICME 2021. My graduation thesis at HHU on this project was awarded as “First Class of Outstanding Graduation Thesis of Jiangsu Province” (江苏省优秀本科毕业论文一等奖).
Fan Liu, Delong Chen (corresponding author), et al. “Self-Supervised Music Motion Synchronization Learning for Music-Driven Conducting Motion Generation”. In Journal of Computer Science Technology, JCST (2022).
