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Visible-infrared cross-modality person re-identification is a challenging ReID task, which aims to retrieve and match the same identity's images between the heterogeneous visible and infrared modalities. Thus, the core of this task is to bridge the huge gap between these two modalities. The existing convolutional neural network-based methods mainly face the problem of insufficient perception of modalities' information, and can not learn good discriminative modality-invariant embeddings forarXiv:2110.08994v1 fatcat:yjkremq7sfbjtdyheplvxg44vm