App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 7

Semantic-guided and mutual information-constrained occluded person re-identification

Deng Xiaohui1
Lin Guorong2
Huang Zhenhua1,2
1. School of Artificial Intelligence, South China Normal University, Foshan Guangdong 528225, China
2. School of Computer Science, South China Normal University, Guangzhou 510631, China
DOI: 10.19734/j.issn.1001-3695.2025.10.0458

Abstract

Occluded person re-identification (Occluded person ReID) aims to match the same pedestrian identity across cameras even when the person is partially occluded. To address the problems of imprecise local feature extraction and redundancy among features in existing CLIP-based text-guided occluded person ReID methods, this paper proposes a Semantic Guidance and Mutual Information Constraint (SGMIC) approach. Specifically, the method introduces an Image Prior Prompt Learning (IPPL) module that employs the CLIP model to generate sample-specific part textual features. It further designs a Segmentation-Guided Part Decoder (SGPD) module to use the generated textual features and semantic segmentation masks for precise disentanglement of body-part local features. In addition, it proposes a Discriminative Information Diversity (DID) loss to reduce redundancy among local features and enhance their discriminability. Experimental results show that on the most challenging Occluded-Duke dataset, the proposed method achieves 66.3% mAP and 75.4% Rank-1, outperforming existing state-of-the-art methods. Moreover, on widely used datasets including Occluded-REID, Market-1501, and DukeMTMC, the proposed method also attains consistent performance improvements over existing approaches, thereby validating its effectiveness.

Foundation Support

国家自然科学基金资助项目(62172166)
广东省基础与应用基础研究基金资助项目(2022A1515011380)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.10.0458
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 7

Publish History

[2026-03-23] Accepted Paper

Cite This Article

邓晓晖, 林国荣, 黄震华. 语义引导与互信息约束的遮挡行人重识别方法 [J]. 计算机应用研究, 2026, 43 (7). (2026-03-24). https://doi.org/10.19734/j.issn.1001-3695.2025.10.0458. (Deng Xiaohui, Lin Guorong, Huang Zhenhua. Semantic-guided and mutual information-constrained occluded person re-identification [J]. Application Research of Computers, 2026, 43 (7). (2026-03-24). https://doi.org/10.19734/j.issn.1001-3695.2025.10.0458. )

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.

Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)