Action Recognition in Still Images With Minimum Annotation Efforts
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Action Recognition in Still Images With Minimum Annotation Efforts
Abstract— The problem of still image-based human action recognition, which essentially involves making prediction by analyzing human poses and their interaction with objects in the scene. Besides image-level action labels (e.g., riding, phoning), during both training and testing stages, existing works usually require additional input of human bounding boxes to facilitate the characterization of the underlying human–object interactions. < final year projects >
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