Watch-n-patch: Unsupervised understanding of actions and relations

Abstract

We focus on modeling human activities comprising multiple actions in a completely unsupervised setting. Our model learns the high-level action co-occurrence and temporal relations between the actions in the activity video. We consider the video as a sequence of short-term action clips, called action-words, and an activity is about a set of action-topics… (More)
DOI: 10.1109/CVPR.2015.7299065

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