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

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 …

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 …

Referring video object segmentation (RVOS) is a challenging language-guided video
grounding task, which requires comprehensively understanding the semantic information of …

Abstract Visible-Infrared Re-Identification (VI-ReID) is challenging in image retrievals. The
modality discrepancy will easily make huge intra-class variations. Most existing methods …

This paper introduces a simple yet powerful channel augmentation for visible-infrared re-
identification. Most existing augmentation operations designed for single-modality visible …

Multispectral pedestrian detection is an important and valuable task in many applications,
which could provide a more accurate and reliable pedestrian detection result by using the …

Daytime visible modality (RGB) and night-time infrared (IR) modality person re-identification
(VI-ReID) is a challenging cross-modality pedestrian retrieval problem. However, training a …

Video person re-identification (V-ReID) can leverage rich spatial-temporal information
embedded in sequence data to achieve better accuracy. However, it is vulnerable to the …

Visible-Infrared person Re-Identification (VI-ReID) conducts comprehensive identity analysis
on non-overlap** visible and infrared camera sets for intelligent surveillance systems …