Affordance2Action: Task-Conditioned Scene-level Affordance Grounding for Real-Time Manipulation
The Affordance2Action (A2A) framework addresses how AI should ground instructions to functional regions in scenes for task-conditioned manipulation. It creates A2A-Bench for supervision and develops a grounding model that converts scene annotations into policy-useful spatial priors, bridging the gap between language understanding and real-time action prediction.