Re-ID is a technology to judge whether there is a specific pedestrian in the image or video. Attention mechanism is applied into Re-ID to optimize the feature representation and improve the discrimination characteristics of features. This paper studies the mechanism of Dual Joint Attention (DJA), which optimizes feature representation by paying attention to local important features and capturing global context in spatial domain and channel domain respectively. And use DJA to build a model. In the classification of the model, A-softmax is used as the loss function which clusters the features in the angle space by imposing the multiplicative angle interval constraint, so as to directly integrate the metric learning into the classification. Experiments show that mAP and Rank-1 are significantly improved.
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