3 papers
cs.CV2024
A Plug-and-Play Physical Motion Restoration Approach for In-the-Wild High-Difficulty Motions
Youliang Zhang, Ronghui Li, Yachao Zhang +4
Extracting physically plausible 3D human motion from videos is a critical task. Although existing simulation-based motion imitation methods can enhance the physical quality of dail…
cs.CV2024
InterDance:Reactive 3D Dance Generation with Realistic Duet Interactions
Ronghui Li, Youliang Zhang, Yachao Zhang +6
Humans perform a variety of interactive motions, among which duet dance is one of the most challenging interactions. However, in terms of human motion generative models, existing w…
cs.CV2024
AToM: Aligning Text-to-Motion Model at Event-Level with GPT-4Vision Reward
Haonan Han, Xiangzuo Wu, Huan Liao +5
Recently, text-to-motion models have opened new possibilities for creating realistic human motion with greater efficiency and flexibility. However, aligning motion generation with…