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Achieve state-of-the-art semantic scene understanding from sparse views with a feed-forward architecture that generalizes across diverse environments.
By explicitly modeling emotion co-occurrence patterns, MPCL achieves state-of-the-art performance in mixed emotion recognition, outperforming existing methods that neglect the structured correlations among coexisting emotions.
Forget static cues: VAGNet grounds 3D object affordances by watching how humans actually use them in videos, significantly improving localization of interaction regions.
