Color-Unrelated Head-Shoulder Networks for Fine-Grained Person Re-identification

doi:10.1145/3599730

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	Color-Unrelated Head-Shoulder Networks for Fine-Grained Person Re-identification
	Xu, Boqiang 1; Liang, Jian 5,6; He, Lingxiao 4; Wu, Jinlin 3,5; Fan, Chao 2; Sun, Zhenan 5,6
刊名	ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS
	2023-11-01
卷号	19 期号:6 页码:21
关键词	Person re-identification fine-grained matching visual surveillance
ISSN号	1551-6857
DOI	10.1145/3599730
通讯作者	Liang, Jian()
英文摘要	Person re-identification (re-id) attempts to match pedestrian images with the same identity across non-overlapping cameras. Existing methods usually study person re-id by learning discriminative features based on the clothing attributes (e.g., color, texture). However, the clothing appearance is not sufficient to distinguish different persons especially when they are in similar clothes, which is known as the fine-grained (FG) person re-id problem. By contrast, this paper proposes to exploit the color-unrelated feature along with the head-shoulder feature for FG person re-id. Specifically, a color-unrelated head-shoulder network (CUHS) is developed, which is featured in three aspects: (1) It consists of a lightweight head-shoulder segmentation layer for localizing the head-shoulder region and learning the corresponding feature. (2) It exploits instance normalization (IN) for learning color-unrelated features. (3) As IN inevitably reduces inter-class differences, we propose to explore richer visual cues for IN by an attention exploration mechanism to ensure high discrimination. We evaluate our model on the FG-reID, Market1501, and DukeMTMC-reID datasets, and the results show that CUHS surpasses previous methods on both the FG and conventional person re-id problems.
资助项目	National Natural Science Foundation of China[62276256] ; Beijing Nova 435 Program[Z211100002121108]
WOS研究方向	Computer Science
语种	英语
出版者	ASSOC COMPUTING MACHINERY
WOS记录号	WOS:001035785200033
资助机构	National Natural Science Foundation of China ; Beijing Nova 435 Program
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/53960]
专题	多模态人工智能系统全国重点实验室
通讯作者	Liang, Jian
作者单位	1.Univ Chinese Acad Sci, 95 Zhongguancun East Rd, Beijing, Peoples R China 2.Chengdu Discaray Technol Co Ltd, 95 Zhongguancun East Rd, Beijing, Peoples R China 3.Chinese Acad Sci, Ctr Artificial Intelligence & Robot, HKISI, 95 Zhongguancun East Rd, Beijing, Peoples R China 4.AI Res JD, 95 Zhongguancun East Rd, Beijing, Peoples R China 5.Chinese Acad Sci, Inst Automat, MAIS, 95 Zhongguancun East Rd, Beijing, Peoples R China 6.Chinese Acad Sci, Inst Automat, CRIPAC, 95 Zhongguancun East Rd, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Xu, Boqiang,Liang, Jian,He, Lingxiao,et al. Color-Unrelated Head-Shoulder Networks for Fine-Grained Person Re-identification[J]. ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS,2023,19(6):21.
APA	Xu, Boqiang,Liang, Jian,He, Lingxiao,Wu, Jinlin,Fan, Chao,&Sun, Zhenan.(2023).Color-Unrelated Head-Shoulder Networks for Fine-Grained Person Re-identification.ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS,19(6),21.
MLA	Xu, Boqiang,et al."Color-Unrelated Head-Shoulder Networks for Fine-Grained Person Re-identification".ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS 19.6(2023):21.