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Feature representation and metric learning are two critical components in person re-identification models. In this paper, we focus on the feature representation and claim that hand-crafted histogram features can be complementary to Convolutional Neural Network (CNN) features. We propose a novel feature extraction model called Feature Fusion Net (FFN) for(More)
Person re-identification is an important problem of matching persons across non-overlapping camera views. However, the re-identification is still far from achieving reliable matching. First, many existing approaches are whole-body-based matching, and how body parts could affect and assist the matching is still not clearly known. Second, the learned(More)
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