SemAnCorr: Semantic Anchored Correspondence for Zero-Shot Manipulation Skill Transfer

arXiv:2607.28382v1 Announce Type: new Abstract: Transferring manipulation skills across object instances that share functionality but differ in geometry remains a fundamental challenge in robot learning. While recent correspondence methods leverage dense visual descriptors and 3D feature fields, nearest-neighbor feature matching often produces spatially incoherent correspondences that fail to recover the local geometric frames required for reliable skill transfer. We introduce SemAnCorr, a train...