In recent years, person re-identification (ReID) has received much attention since it is a
fundamental task in intelligent surveillance systems and has widespread application …

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 …

For the visible-infrared person re-identification (VIReID) task, one of the major challenges is
the modality gaps between visible (VIS) and infrared (IR) images. However, the training …

This paper tackles the cross-modality person re-identification (re-ID) problem by
suppressing the modality discrepancy. In cross-modality re-ID, the query and gallery images …

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 …

Visible-infrared person re-identification (Re-ID) aims to match the pedestrian images of the
same identity from different modalities. Existing works mainly focus on alleviating the …

RGB-Infrared person re-identification (RGB-IR ReID) is a challenging cross-modality
retrieval problem, which aims at matching the person-of-interest over visible and infrared …

Modern data augmentation using a mixture-based technique can regularize the models from
overfitting to the training data in various computer vision applications, but a proper data …

Existing fully-supervised person re-identification (ReID) methods usually suffer from poor
generalization capability caused by domain gaps. The key to solving this problem lies in …