5 papers
Flow6D: Discrete-to-Continuous Flow Matching for Efficient and Accurate Category-Level 6D Pose Estimation
Mingyu Mei, Li Zhang, Zibo Dai +4
6D pose estimation is a key task in computer vision and embodied AI, widely used in robotic manipulation, augmented reality, etc. Existing methods directly regress in a high-dimens…
Force Policy: Learning Hybrid Force-Position Control Policy under Interaction Frame for Contact-Rich Manipulation
Hongjie Fang, Shirun Tang, Mingyu Mei +9
Contact-rich manipulation demands human-like integration of perception and force feedback: vision should guide task progress, while high-frequency interaction control must stabiliz…
DICArt: Advancing Category-level Articulated Object Pose Estimation in Discrete State-Spaces
Li Zhang, Mingyu Mei, Ailing Wang +7
Articulated object pose estimation is a core task in embodied AI. Existing methods typically regress poses in a continuous space, but often struggle with 1) navigating a large, com…
Auto3R: Automated 3D Reconstruction and Scanning via Data-driven Uncertainty Quantification
Chentao Shen, Sizhe Zheng, Bingqian Wu +5
Traditional high-quality 3D scanning and reconstruction typically relies on human labor to plan the scanning procedure. With the rapid development of embodied systems such as drone…
Active Control Points-based 6DoF Pose Tracking for Industrial Metal Objects
Chentao Shen, Ding Pan, Mingyu Mei +2
Visual pose tracking is playing an increasingly vital role in industrial contexts in recent years. However, the pose tracking for industrial metal objects remains a challenging tas…