AffordMatcher: Affordance Learning in 3D Scenes from Visual Signifiers

ArXi:2603.27970v1 Announce Type: new Affordance learning is a complex challenge in many applications, where existing approaches primarily focus on the geometric structures, visual knowledge, and affordance labels of objects to determine interactable regions. However, extending this learning capability to a scene is significantly complicated, as incorporating object- and scene-level semantics is not straightforward. In this work, we