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Recent years have witnessed significant progress in detection of basic human actions. However, most existing methods rely on assumptions such as known spatial locations and temporal segmentations or employ very computationally expensive approaches such as sliding window search through a spatio-temporal volume. It is difficult for such methods to scale up to handle the challenges in real applications...
In this paper, we investigate the detection of semantic human actions in complex scenes. Unlike conventional action recognition in well-controlled environments, action detection in complex scenes suffers from cluttered backgrounds, heavy crowds, occluded bodies, and spatial-temporal boundary ambiguities caused by imperfect human detection and tracking. Conventional algorithms are likely to fail with...
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