ICLR2025

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo

Junzhe Zhu, Yuanchen Ju, Junyi Zhang, Muhan Wang, Zhecheng Yuan, Kaizhe Hu, Huazhe Xu

摘要

Figure 1: (a) Zero-shot color transfer between 3D assets. (b) In real-world robotic experiments, we use DenseMatcher to transfer a manipulation sequence to the robot from a single human demonstration. Circles represent the contact points in the human demo / grasping points for robot manipulation.