4 papers · 1 filter
OCRA: Object-Centric Learning with 3D and Tactile Priors for Human-to-Robot Action Transfer
Kuanning Wang, Ke Fan, Yuqian Fu +6
We present OCRA, an Object-Centric framework for video-based human-to-Robot Action transfer that learns directly from human demonstration videos to enable robust manipulation. Obje…
Learning Generalizable Hand-Object Tracking from Synthetic Demonstrations
Yinhuai Wang, Runyi Yu, Hok Wai Tsui +9
We present a system for learning generalizable hand-object tracking controllers purely from synthetic data, without requiring any human demonstrations. Our approach makes two key c…
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…
AnchorDP3: 3D Affordance Guided Sparse Diffusion Policy for Robotic Manipulation
Ziyan Zhao, Ke Fan, He-Yang Xu +5
We present AnchorDP3, a diffusion policy framework for dual-arm robotic manipulation that achieves state-of-the-art performance in highly randomized environments. AnchorDP3 integra…