Action is in the Eye of the Beholder: Eye-gaze Driven Model for Spatio-Temporal Action Localization

NeurIPS 2013 Nataliya ShapovalovaMichalis RaptisLeonid SigalGreg Mori

We propose a new weakly-supervised structured learning approach for recognition and spatio-temporal localization of actions in video. As part of the proposed approach we develop a generalization of the Max-Path search algorithm, which allows us to efficiently search over a structured space of multiple spatio-temporal paths, while also allowing to incorporate context information into the model... (read more)

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