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cs.CV2026
Controllable Text-to-Motion Generation via Modular Body-Part Phase Control
Minyue Dai, Ke Fan, Anyi Rao +2
Text-to-motion (T2M) generation is becoming a practical tool for animation and interactive avatars. However, modifying specific body parts while maintaining overall motion coherenc…
cs.CV2025
Go to Zero: Towards Zero-shot Motion Generation with Million-scale Data
Ke Fan, Shunlin Lu, Minyue Dai +6
Generating diverse and natural human motion sequences based on textual descriptions constitutes a fundamental and challenging research area within the domains of computer vision, g…
cs.CV2025
Towards Synthesized and Editable Motion In-Betweening Through Part-Wise Phase Representation
Minyue Dai, Ke Fan, Bin Ji +5
Styled motion in-betweening is crucial for computer animation and gaming. However, existing methods typically encode motion styles by modeling whole-body motions, often overlooking…