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arXiv · 2410.22626

Symbolic Graph Inference for Compound Scene Understanding

FNU Aryan·Simon Stepputtis·Sarthak Bhagat·Joseph Campbell·Kwonjoon Lee·Hossein Nourkhiz Mahjoub·Katia Sycara
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Abstract

Scene understanding is a fundamental capability needed in many domains, ranging from question-answering to robotics. Unlike recent end-to-end approaches that must explicitly learn varying compositions of the same scene, our method reasons over their constituent objects and analyzes their arrangement to infer a scene's meaning. We propose a novel approach that reasons over a scene's scene- and knowledge-graph, capturing spatial information while being able to utilize general domain knowledge in a joint graph search. Empirically, we demonstrate the feasibility of our method on the ADE20K dataset and compare it to current scene understanding approaches.

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FNU Aryan, Simon Stepputtis, Sarthak Bhagat, Joseph Campbell, Kwonjoon Lee, Hossein Nourkhiz Mahjoub, Katia Sycara. 2024-10-30. Symbolic Graph Inference for Compound Scene Understanding. https://arxiv.org/abs/2410.22626

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