DW-ReID: Vision-Language Learning for Person Re-Identification Under Diverse Weather Conditions.

Lei Cai, Yuying Liang, Bin Wang, Hexi Li, Jinquan Yang, Tao Zhu

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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5 · Who and what money

Authors and funding

6 authors.

Lei CaiCollege of Engineering, Huaqiao University, Quanzhou 362021, China.ORCID 0009-0009-6020-1609

Yuying LiangSchool of Computing, Guangzhou College of Applied Science and Technology, Zhaoqing 526072, China.ORCID 0009-0008-6005-0794

Bin WangSchool of Computer Science and Cyber Engineering, Guangzhou University, Guangzhou 510006, China.ORCID 0009-0002-1197-8509

Hexi LiSchool of Computing, Guangzhou College of Applied Science and Technology, Zhaoqing 526072, China.

Jinquan YangSchool of Computing, Guangzhou College of Applied Science and Technology, Zhaoqing 526072, China.

Tao ZhuSchool of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541004, China.

Funding

National Natural Science Foundation of China 62261011Natural Science Foundation of Fujian Province 2024J01098Natural Science Foundation of Guangxi Province 2025JJA170157Natural Science Foundation of Xiamen, China 3502Z202472011Scientific Research Funds of Huaqiao University 24BS109

6 · The paper itself

Abstract

Person re-identification (ReID) under diverse weather conditions remains a critical yet insufficiently explored problem. Most existing ReID approaches are developed and benchmarked on clear-weather datasets, resulting in significant performance degradation when deployed in rainy, snowy, or hazy environments. Conventional image restoration methods, typically optimized for low-level image quality metrics, are often misaligned with the objectives of high-level identity discrimination and thus fail to improve the person ReID performance. To address these limitations, we propose DW-ReID, a

Indexed as

adverse weatherperson re-identificationvision–language learning

Identifiers

PMID41978048

DOI10.3390/s26072263

PMCPMC13075237

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.