We address the problem of visible-infrared person re-identification (VI-reID), that is,
retrieving a set of person images, captured by visible or infrared cameras, in a cross-modal …

Abstract For Visible-Infrared person Re-IDentification (VI-ReID), existing modality-specific
information compensation based models try to generate the images of missing modality from …

Visible-infrared person re-identification (VI-ReID) is an important task in night-time
surveillance applications, since visible cameras are difficult to capture valid appearance …

Visible-infrared person re-identification (VI-ReID) is a challenging task in computer vision,
aiming at matching people across images from visible and infrared modalities. The widely …

Visible-infrared person re-identification (ReID) aims to recognize a same person of interest
across a network of RGB and IR cameras. Some deep learning (DL) models have directly …

Visible-Infrared Person Re-Identification (VI-ReID) has become an emerging task for night-
time surveillance systems. In order to reduce the cross-modality discrepancy, previous works …

Visible-infrared person re-identification (VI-ReID) is a challenging task due to the large cross-
modality discrepancies and intra-class variations. Existing works mainly focus on learning …

Visible-infrared person re-identification (VI-ReID) is a challenging task due to large cross-
modality discrepancies and intra-class variations. Existing methods mainly focus on learning …

Visible-infrared person re-identification (VI-ReID) focuses on matching the pedestrian
images of the same identity captured by different modality cameras. The part-based methods …

Unsupervised learning visible-infrared person re-identification (USL-VI-ReID) is an
extremely important and challenging task, which can alleviate the issue of expensive cross …