collaborators

6 papers

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.RO2025

UniTracker: Learning Universal Whole-Body Motion Tracker for Humanoid Robots

Kangning Yin, Weishuai Zeng, Ke Fan +7

Achieving expressive and generalizable whole-body motion control is essential for deploying humanoid robots in real-world environments. In this work, we propose UniTracker, a three…

cs.RO2025

Behavior Foundation Model for Humanoid Robots

Weishuai Zeng, Shunlin Lu, Kangning Yin +4

Whole-body control (WBC) of humanoid robots has witnessed remarkable progress in skill versatility, enabling a wide range of applications such as locomotion, teleoperation, and mot…

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…

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.RO2025

SMAP: Self-supervised Motion Adaptation for Physically Plausible Humanoid Whole-body Control

Haoyu Zhao, Sixu Lin, Qingwei Ben +5

This paper presents a novel framework that enables real-world humanoid robots to maintain stability while performing human-like motion. Current methods train a policy which allows…