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cs.CV2026
MoVT: Video-Augmented Motion Tokenizer for Text-to-Motion Generation
Beibei Jing, Tianle Guo, Youjia Zhang +5
Text-driven 3D human motion generation models face significant challenges in responding to diverse and unconstrained textual prompts, primarily due to the limited availability of 3…
cs.CV2026
UniMoFlow: Grounding Instruction-Driven 3D Human Motion Editing in Generation
Yilei Hua, Beibei Jing, Ce Zheng +3
Instruction-driven editing of 3D human motion requires precise spatiotemporal localization, rich semantic grounding, and strict preservation of unmodified content. Existing methods…
cs.CV2023
AMD:Anatomical Motion Diffusion with Interpretable Motion Decomposition and Fusion
Beibei Jing, Youjia Zhang, Zikai Song +2
Generating realistic human motion sequences from text descriptions is a challenging task that requires capturing the rich expressiveness of both natural language and human motion.…