Feature Calibration Network for Occluded Pedestrian Detection

IEEE Transactions on Intelligent Transportation Systems(2022)

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摘要
Pedestrian detection in the wild remains a challenging problem especially for scenes containing serious occlusion. In this paper, we propose a novel feature learning method in the deep learning framework, referred to as Feature Calibration Network (FC-Net), to adaptively detect pedestrians under various occlusions. FC-Net is based on the observation that the visible parts of pedestrians are select...
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关键词
Feature extraction,Calibration,Detectors,Deep learning,Visualization,Training,Object detection
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