Deep Coattention-Based Comparator for Relative Representation Learning in Person Re-Identification
IEEE transactions on neural networks and learning systems, 2020.
Person re-identification (re-ID) favors discriminative representations over unseen shots to recognize identities in disjoint camera views. Effective methods are developed via pair-wise similarity learning to detect a fixed set of region features, which can be mapped to compute the similarity value. However, relevant parts of each image ar...More
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