Person re-identification (Re-ID) technology plays an increasingly crucial role in intelligent
surveillance systems. Widespread occlusion significantly impacts the performance of person …

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 …

The fusion of infrared and visible images aims to generate a composite image that can
simultaneously contain the thermal radiation information of an infrared image and the …

Due to the modality gap between visible and infrared images with high visual ambiguity,
learning diverse modality-shared semantic concepts for visible-infrared person re …

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 …

This paper introduces a powerful channel augmented joint learning strategy for the visible-
infrared recognition problem. For data augmentation, most existing methods directly adopt …

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 …

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 (VI-ReID) is a cross-modality retrieval problem,
which aims at matching the same pedestrian between the visible and infrared cameras. Due …