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PSEE: Progressive Sensor Event Expansion for Point-Supervised Temporal Action Localization
Temporal action localization (TAL) in wearable sensor streams identifies action classes and temporal boundaries, enabling finer-grained activity understanding than conventional action recognition. However, training typically requires costly start--end annotations for every action instance. To reduce this burden, we study point-supervised TAL, where each instance is labeled with only one timestamp and its class. We propose Progressive Sensor Event Expansion (PSEE), which combines semantic activations, sensor-specific transition evidence, and adaptive temporal ownership to recover point-supervis
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-18T08:11:51.000Z
First collected: 2026-09-23T14:01:59.594Z. This is not the publication date.