{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T03:01:28Z","timestamp":1760151688642,"version":"build-2065373602"},"reference-count":60,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2022,3,30]],"date-time":"2022-03-30T00:00:00Z","timestamp":1648598400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61402540","60903222","61672538","61272024"],"award-info":[{"award-number":["61402540","60903222","61672538","61272024"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Existing person re-recognition (Re-ID) methods usually suffer from poor generalization capability and over-fitting problems caused by insufficient training samples. We find that high-level attributes, semantic information, and part-based local information alignment are useful for person Re-ID networks. In this study, we propose a person re-recognition network with part-based attribute-enhanced features. The model includes a multi-task learning module, local information alignment module, and global information learning module. The ResNet based on non-local and instance batch normalization (IBN) learns more discriminative feature representations. The multi-task module, local module, and global module are used in parallel for feature extraction. To better prevent over-fitting, the local information alignment module transforms pedestrian attitude alignment into local information alignment to assist in attribute recognition. Extensive experiments are carried out on the Market-1501 and DukeMTMC-reID datasets, whose results demonstrate that the effectiveness of the method is superior to most current algorithms.<\/jats:p>","DOI":"10.3390\/a15040120","type":"journal-article","created":{"date-parts":[[2022,3,30]],"date-time":"2022-03-30T21:22:14Z","timestamp":1648675334000},"page":"120","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Multi-Level Fusion Model for Person Re-Identification by Attribute Awareness"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0924-3079","authenticated-orcid":false,"given":"Shengyu","family":"Pei","sequence":"first","affiliation":[{"name":"School of Automation, Central South University, Changsha 410075, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0172-4070","authenticated-orcid":false,"given":"Xiaoping","family":"Fan","sequence":"additional","affiliation":[{"name":"School of Automation, Central South University, Changsha 410075, China"},{"name":"School of Information Technology and Management, Hunan University of Finance and Economics, Changsha 410205, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"15519","DOI":"10.1007\/s00500-020-04880-1","article-title":"Ranking-based triplet loss function with intra-class mean and variance for fine-grained classification tasks","volume":"24","author":"Bhattacharya","year":"2020","journal-title":"Soft Comput."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"5729","DOI":"10.1007\/s00500-016-2150-x","article-title":"Adaptive image segmentation based on color clustering for person re-identification","volume":"21","author":"Zhang","year":"2017","journal-title":"Soft Comput."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Ye, M., Shen, J., Lin, G., Xiang, T., Shao, L., and Hoi, S.C.H. 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