1 citations · 1 across the 4 of their papers we have counts for
4 papers
Personalized Cross-Modal Emotional Correlation Learning for Speech-Preserving Facial Expression Manipulation
Tianshui Chen, Yujie Zhu, Jianman Lin +4
Speech-preserving facial expression manipulation (SPFEM) aims to enhance human expressiveness without altering mouth movements tied to the original speech. A primary challenge in t…
OpenDance: Multimodal Controllable 3D Dance Generation with Large-scale Internet Data
Jinlu Zhang, Zixi Kang, Libin Liu +4
Music-driven 3D dance generation offers significant creative potential, yet practical applications demand versatile and multimodal control. As the highly dynamic and complex human…
Aligning Human Motion Generation with Human Perceptions
Haoru Wang, Wentao Zhu, Luyi Miao +4
Human motion generation is a critical task with a wide range of applications. Achieving high realism in generated motions requires naturalness, smoothness, and plausibility. Despit…
Human Motion Generation: A Survey
Wentao Zhu, Xiaoxuan Ma, Dongwoo Ro +6
Human motion generation aims to generate natural human pose sequences and shows immense potential for real-world applications. Substantial progress has been made recently in motion…