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arXiv · 2507.14426

CRAFT: A Neuro-Symbolic Framework for Visual Functional Affordance Grounding

Zhou Chen·Joe Lin·Sathyanarayanan N. Aakur
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Abstract

We introduce CRAFT, a neuro-symbolic framework for interpretable affordance grounding, which identifies the objects in a scene that enable a given action (e.g., "cut"). CRAFT integrates structured commonsense priors from ConceptNet and language models with visual evidence from CLIP, using an energy-based reasoning loop to refine predictions iteratively. This process yields transparent, goal-driven decisions to ground symbolic and perceptual structures. Experiments in multi-object, label-free settings demonstrate that CRAFT enhances accuracy while improving interpretability, providing a step toward robust and trustworthy scene understanding.

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Zhou Chen, Joe Lin, Sathyanarayanan N. Aakur. 2025-07-19. CRAFT: A Neuro-Symbolic Framework for Visual Functional Affordance Grounding. https://arxiv.org/abs/2507.14426

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