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Convolutional neural network (CNN) based face detectors are inefficient in handling faces of diverse scales. They rely on either fitting a large single model to faces across a large scale range or multi-scale testing. Both are computationally expensive. We propose Scale-aware Face Detection (SAFD) to handle scale explicitly using CNN, and achieve better performance with less computation cost. Prior...
In this paper we present a novel approach for discrimination of frontal face in video, using integral channel features(ICF) and Adaboost. We have two stages for this approach based on classification, the first stage is training process, we utilize ICF exacted from training database to train strong classifier, which is implemented by Adaboost. The second stage is discriminating process by scoring,...
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