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Unsupervised learning visible-infrared person re-identification (USL-VI-ReID) aims at learning modality-invariant features from unlabeled cross-modality dataset, which is crucial for practical applications in video surveillance systems. The key to ...

Visible infrared person re-identification (VI-ReID) aims at searching out the corresponding infrared (visible) images from a gallery set captured by other spectrum cameras. Recent works mainly focus on supervised VI-ReID methods that require plenty of ...

Because the imaging spectra of infrared images and visible light images are different, there is a huge modal difference between visible light images and infrared ones. Existing methods use image conversion to solve the problem of modal ...

• We propose an image pair generation module, which can separate the modal information and attribute information of the image and realize arbitrary modal ...

Person re-identification (re-id) has received ever-increasing research focus, because of its important role in video surveillance applications. This paper addresses the re-id problem between visible images of color cameras and infrared images of ...

With explosive surveillance data during day and night, visible-infrared person re-identification (VI-ReID) is an emerging challenge due to the apparent cross-modality discrepancy between visible and infrared images. Existing VI-ReID work mainly focuses ...