A synthesis protocol builds a regenerable four-level intention benchmark from flat action data and shows a consistent compositional held-out gap across four baseline model families.
Enhancing action recognition by leveraging the hierarchical structure of actions and textual context
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Compositional Benchmark Synthesis for Hierarchical Human Action Recognition
A synthesis protocol builds a regenerable four-level intention benchmark from flat action data and shows a consistent compositional held-out gap across four baseline model families.