Multimodal image matching, which refers to identifying and then corresponding the same or
similar structure/content from two or more images that are of significant modalities or …

Person re-identification (Re-ID) aims at retrieving a person of interest across multiple non-
overlapping cameras. With the advancement of deep neural networks and increasing …

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

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 …

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 …

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 …

Cross-modality person re-identification is a challenging task due to large cross-modality
discrepancy and intra-modality variations. Currently, most existing methods focus on …

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 …