Learning Deep RGBT Representations for Robust Person Re-identification

doi:10.1007/s11633-020-1262-z

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	Learning Deep RGBT Representations for Robust Person Re-identification
	Ai-Hua Zheng; Zi-Han Chen; Cheng-Long Li; Jin Tang; Bin Luo
刊名	International Journal of Automation and Computing
	2021
卷号	18 期号:3 页码:443-456
关键词	Person re-identification (Re-ID) thermal infrared generative networks attention deep learning
ISSN号	1476-8186
DOI	10.1007/s11633-020-1262-z
英文摘要	Person re-identification (Re-ID) is the scientific task of finding specific person images of a person in a non-overlapping camera networks, and has achieved many breakthroughs recently. However, it remains very challenging in adverse environmental conditions, especially in dark areas or at nighttime due to the imaging limitations of a single visible light source. To handle this problem, we propose a novel deep red green blue (RGB)-thermal (RGBT) representation learning framework for a single modality RGB person Re-ID. Due to the lack of thermal data in prevalent RGB Re-ID datasets, we propose to use the generative adversarial network to translate labeled RGB images of person to thermal infrared ones, trained on existing RGBT datasets. The labeled RGB images and the synthetic thermal images make up a labeled RGBT training set, and we propose a cross-modal attention network to learn effective RGBT representations for person Re-ID in day and night by leveraging the complementary advantages of RGB and thermal modalities. Extensive experiments on Market1501, CUHK03 and DukeMTMC-reID datasets demonstrate the effectiveness of our method, which achieves state-of-the-art performance on all above person Re-ID datasets
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/44293]
专题	自动化研究所_学术期刊_International Journal of Automation and Computing
作者单位	Anhui Provincial Key Laboratory of Multi-modal Cognitive Computation, School of Computer Science and Technology, Anhui University, Hefei 230601, China
推荐引用方式 GB/T 7714	Ai-Hua Zheng,Zi-Han Chen,Cheng-Long Li,et al. Learning Deep RGBT Representations for Robust Person Re-identification[J]. International Journal of Automation and Computing,2021,18(3):443-456.
APA	Ai-Hua Zheng,Zi-Han Chen,Cheng-Long Li,Jin Tang,&Bin Luo.(2021).Learning Deep RGBT Representations for Robust Person Re-identification.International Journal of Automation and Computing,18(3),443-456.
MLA	Ai-Hua Zheng,et al."Learning Deep RGBT Representations for Robust Person Re-identification".International Journal of Automation and Computing 18.3(2021):443-456.