中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 自动化研究所
  3. 中国科学院自动化研究所
  4. 多模态人工智能系统全国重点实验室
Color-Unrelated Head-Shoulder Networks for Fine-Grained Person Re-identification

文献类型：期刊论文

作者Xu, Boqiang2; Liang, Jian1,3; He, Lingxiao4; Wu, Jinlin3,5; Fan, Chao6; Sun, Zhenan1,3
刊名ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS
出版日期2023-11-01
卷号19期号:6页码:21
ISSN号1551-6857
关键词Person re-identification fine-grained matching visual surveillance
DOI10.1145/3599730
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
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.Chinese Acad Sci, Inst Automat, CRIPAC, 95 Zhongguancun East Rd, Beijing, Peoples R China
2.Univ Chinese Acad Sci, 95 Zhongguancun East Rd, Beijing, Peoples R China
3.Chinese Acad Sci, Inst Automat, MAIS, 95 Zhongguancun East Rd, Beijing, Peoples R China
4.AI Res JD, 95 Zhongguancun East Rd, Beijing, Peoples R China
5.Chinese Acad Sci, Ctr Artificial Intelligence & Robot, HKISI, 95 Zhongguancun East Rd, Beijing, Peoples R China
6.Chengdu Discaray Technol Co Ltd, 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.

入库方式： OAI收割

来源：自动化研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。