Unlocking 3D Affordance Segmentation with 2D Semantic Knowledge

ArXi:2510.08316v2 Announce Type: replace Affordance segmentation aims to decompose 3D objects into parts that serve distinct functional roles, enabling models to reason about object interactions rather than mere recognition. Existing methods, mostly following the paradigm of 3D semantic segmentation or prompt-based frameworks, struggle when geometric cues are weak or ambiguous, as sparse point clouds provide limited functional information.