AFUN: Towards an Affordance Foundation Model for Functionality Understanding
- Published
- Source
- arXiv
- Paper number
- 302
- Field
- Robotics
- arXiv ID
- 2606.02551
Key points
- Existing methods usually cover only part of this task; they either localize task-relevant regions without specifying executable actions, or they predict actions but remain limited in scalability.
- This paper presents ourmodel, a step toward an affordance foundation model for functionality understanding.
- From a single RGB-D observation and a natural-language task description, ourmodel predicts a task-conditioned functionality mask that indicates where to interact and a 3D post-contact action curve that indicates how to interact.
Paper links
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