2025-01-14-lin25a.md

title	booktitle	year	volume	series	month	publisher	pdf	url	openreview	abstract	layout	issn	id	tex_title	firstpage	lastpage	page	order	cycles	bibtex_editor	editor	bibtex_author	author	date	address	container-title	genre	issued	extras
Visible-Infrared Person Re-Indentification via Feature Fusion and Deep Mutual Learning	Proceedings of the 16th Asian Conference on Machine Learning	2025	260	Proceedings of Machine Learning Research	0	PMLR	https://raw.githubusercontent.com/mlresearch/v260/main/assets/lin25a/lin25a.pdf	https://proceedings.mlr.press/v260/lin25a.html	NmoEsT5Rul	Visible-Infrared Person Re-Identification (VI-ReID) aims to retrieve a set of person images captured from both visible and infrared camera views. Addressing the challenge of modal differences between visible and infrared images, we propose a VI-ReID network based on Feature Fusion and Deep Mutual Learning (DML). To enhance the model’s robustness to color, we introduce a novel data augmentation method called Random Combination of Channels (RCC), which generates new images by randomly combining R, G, and B channels of visible images. Furthermore, to capture more informative features of individuals, we fuse the features from the middle layer of the network. To reduce the model’s dependence on global features, we employ a fusion branch as an auxiliary branch, facilitating synchronous learning of global and fusion branches through Deep Mutual Learning . Extensive experiments on the SYSU-MM01 and RegDB datasets validate the superiority of our method, showcasing its excellent performance when compared to other state-of-the-art approaches.	inproceedings	2640-3498	lin25a	Visible-Infrared Person Re-Indentification via Feature Fusion and Deep Mutual Learning	79	94	79-94	79	false	Nguyen, Vu and Lin, Hsuan-Tien	given family Vu Nguyen given family Hsuan-Tien Lin	Lin, Ziyang and Wang, Banghai	given family Ziyang Lin given family Banghai Wang	2025-01-14		Proceedings of the 16th Asian Conference on Machine Learning	inproceedings	date-parts 2025 1 14