eSEC-LAM converts enriched Semantic Event Chains into symbolic states via foundation-model perception and deterministic predicate extraction, yielding competitive action recognition, improved next-primitive prediction, and greater robustness than pure symbolic or end-to-end baselines on EPIC-KITCHEN
2020.Spatio-temporal reasoning for semantic scene understanding and its application in recognition and prediction of manipulation actions in image sequences
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Neuro-Symbolic Manipulation Understanding with Enriched Semantic Event Chains
eSEC-LAM converts enriched Semantic Event Chains into symbolic states via foundation-model perception and deterministic predicate extraction, yielding competitive action recognition, improved next-primitive prediction, and greater robustness than pure symbolic or end-to-end baselines on EPIC-KITCHEN