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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...
This paper targets on the problem of set to set recognition, which learns the metric between two image sets. Images in each set belong to the same identity. Since images in a set can be complementary, they hopefully lead to higher accuracy in practical applications. However, the quality of each sample cannot be guaranteed, and samples with poor quality will hurt the metric. In this paper, the quality...
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,...
A novel facial expression recognition method based on sparse representation (SR) is proposed. To enhance the effect of important face region, fisher separation criterion is introduced to calculate the weight of local binary patterns (LBP) patches. Expression recognition technique using the new mathematical theory from sparse representation an compressive sensing is proposed, and the improvements in...
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