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Person re-identification from text to image based on mutual teaching

Text-based cross-modal person re-identification refers to the retrieval of the corresponding identity image in the pedestrian image set through the linguistic description of the pedestrian. Aiming at the problem that there is no interaction between the image-text feature extraction branch, we propose a text-to-image person re-identification method based on mutual teaching. The proposed method adds interactive operation in the image text feature extraction part to make the image and text information respectively guide the feature extraction of another modality, which realizes the information transfer between image and text modalities to close the distance between two modalities. The method is experimentally verified on the CUHK-PEDES dataset. The experimental results show the effectiveness and superiority of the proposed method.