Visible-infrared cross-modality person re-identification (VI-ReID) is currently a prevalent but
challenging research topic in computer vision, since it can remedy the poor performance of …

Image colorization, as an essential problem in computer vision (CV), has attracted an
increasing amount of researchers attention in recent years, especially deep learning-based …

Visible-infrared person re-identification (VI-ReID) is an emerging and challenging cross-
modality image matching problem because of the explosive surveillance data in night-time …

Abstract RGB-Thermal infrared (RGB-T) image analysis has been actively studied in recent
years. In the past decade, it has received wide attention and made a lot of important …

Visible-Infrared person reidentification (VI-ReID) is a challenging matching problem due to
large modality variations between visible and infrared images. Existing approaches usually …

Visible-infrared person re-identification (VI-ReID) is a challenging and essential task that
aims to retrieve a set of person images over visible and infrared camera views. In order to …

Visible-infrared person re-identification (VI-ReID) aims to search the same pedestrian
images across different modalities, which is a challenging task for video surveillance …

Learning about appearance embedding is of great importance for a variety of different
computer-vision applications, which has prompted a surge in person re-identification (Re-ID) …

Person re-identification (ReID) plays a crucial role in video surveillance with the aim to
search a specific person across disjoint cameras, and it has progressed notably in recent …

RGB-infrared cross-modality person re-identification is a challenging image retrieval task
due to the intra-class variations and cross-modality discrepancy. However, it is insufficient …