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We present a method for object detection combining the effectiveness of a set of mid-level parts. These parts are learned weak-supervised from object bounding box annotations. The approach based part models can handle the detection of objects across changes in viewpoint, intraclass variability and object deformation. The objects are localized by the detected parts with learned information of location...
Recent methods based on mid-level visual concepts have shown promising capability in human action recognition field. Automatically discovering semantic entities such as parts for an action class remains challenging. In this paper, we focus on discovering distinctive action parts for recognition of human actions by learning and selecting a small number of discriminative part detectors directly from...
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