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Hugging Face Trending Papers

Joint Class-Time Learning for Video Classification with Multi-Instance Partial-Label Learning

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The paper introduces PIVOTMIPL, a method for video classification that tackles multi‑instance partial‑label learning by jointly assigning classes and temporal evidence. It uses occupancy‑regularized spherical matching to link contextualized video features with nonuniform temporal mass, and a dual‑marginal KL projection to build a structured teacher that refines class beliefs while maintaining temporal occupancy. Experiments on VCMIPL benchmarks derived from Breakfast, DoTA, and FineAction show that PIVOTMIPL outperforms existing MIPL algorithms in both effectiveness and efficiency.

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