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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 4
1220-1225,1255

Support pair active learning for person re-identification

Jin Dapeng
Li Minxian
School of Computer Science & Engineering, Nanjing University of Science & Technology, Nanjing 210094, China
DOI: 10.19734/j.issn.1001-3695.2022.08.0393

Abstract

Supervised-learning based person re-identification requires a large amount of manual labeled data, which is not applicable in practical deployment. This paper proposed a support pairs active learning(SPAL) re-identification framework to lower the manual labeling cost for large-scale person re-identification. Specifically, this paper built a kind of unsupervised active learning framework, and it designed a dual uncertainty selection strategy to iteratively discover support pairs and required human annotations in this framework. Afterwards, it introduced a constrained clustering algorithm to propagate the relationships of labeled support pairs to other unlabeled samples. Moreover, it proposed a hybrid learning strategy consisting of an unsupervised contrastive loss and a supervised support pairs loss to learn the discriminative feature representation. On large-scale person re-identification dataset MSMT17, compared with the state-of-the-art methods, the labeling cost of the proposed method is reduced by 64%, mAP and rank1 are increased by 11.0% and 14.9% respectively. Extensive experiments demonstrate that it can effectively lower the labeling cost and is superior to state-of-the-art unsupervised active learning person re-identification methods.

Foundation Support

国家自然科学基金资助项目(62076132)
江苏省自然科学基金资助项目(BK20211194)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.08.0393
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 4
Section: Technology of Graphic & Image
Pages: 1220-1225,1255
Serial Number: 1001-3695(2023)04-042-1220-06

Publish History

[2022-10-19] Accepted Paper
[2023-04-05] Printed Article

Cite This Article

金大鹏, 李旻先. 基于支持对挖掘的主动学习行人再识别 [J]. 计算机应用研究, 2023, 40 (4): 1220-1225,1255. (Jin Dapeng, Li Minxian. Support pair active learning for person re-identification [J]. Application Research of Computers, 2023, 40 (4): 1220-1225,1255. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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