{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T01:54:27Z","timestamp":1769565267752,"version":"3.49.0"},"reference-count":53,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Signal Processing: Image Communication"],"published-print":{"date-parts":[[2026,3]]},"DOI":"10.1016\/j.image.2025.117462","type":"journal-article","created":{"date-parts":[[2025,12,30]],"date-time":"2025-12-30T16:56:52Z","timestamp":1767113812000},"page":"117462","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["MAPLE: Combination of multiple angles of view and enhanced pseudo-label generation for unsupervised person re-identification"],"prefix":"10.1016","volume":"142","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-0829-836X","authenticated-orcid":false,"given":"Mai T.","family":"Do","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5097-2401","authenticated-orcid":false,"given":"Anh D.","family":"Nguyen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.image.2025.117462_b1","series-title":"Exploiting sample uncertainty for domain adaptive person re-identification","first-page":"3538","author":"Zheng","year":"2021"},{"key":"10.1016\/j.image.2025.117462_b2","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2024.111471","article-title":"Gan-based data augmentation and pseudo-label refinement with holistic features for unsupervised domain adaptation person re-identification","volume":"288","author":"Pham","year":"2024","journal-title":"Knowl.-Based Syst."},{"key":"10.1016\/j.image.2025.117462_b3","doi-asserted-by":"crossref","first-page":"3527","DOI":"10.1049\/iet-ipr.2020.0166","article-title":"Progressive learning with style transfer for distant domain adaptation","volume":"14","author":"Xiang","year":"2020","journal-title":"IET Image Process."},{"key":"10.1016\/j.image.2025.117462_b4","first-page":"11309","article-title":"Self-paced contrastive learning with hybrid memory for domain adaptive object re-id","volume":"vol. 33","author":"Ge","year":"2020"},{"key":"10.1016\/j.image.2025.117462_b5","series-title":"2021 7th IEEE International Conference on Network Intelligence and Digital Content","first-page":"91","article-title":"Hard-sample guided hybrid contrast learning for unsupervised person re-identification","author":"Hu","year":"2021"},{"key":"10.1016\/j.image.2025.117462_b6","series-title":"2022 IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"7298","article-title":"Part-based pseudo label refinement for unsupervised person re-identification","author":"Cho","year":"2022"},{"key":"10.1016\/j.image.2025.117462_b7","doi-asserted-by":"crossref","unstructured":"H. Chen, B. Lagadec, F. Bremond, Ice: Inter-instance contrastive encoding for unsupervised person re-identification, in: Proceedings of the IEEE\/CVF International Conference on Computer Vision, (ICCV), 2021, pp. 14960\u201314969.","DOI":"10.1109\/ICCV48922.2021.01469"},{"key":"10.1016\/j.image.2025.117462_b8","series-title":"2020 7th International Forum on Electrical Engineering and Automation","first-page":"949","article-title":"Dbscan clustering algorithm based on density","author":"Deng","year":"2020"},{"key":"10.1016\/j.image.2025.117462_b9","series-title":"2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"13654","article-title":"Hierarchical clustering with hard-batch triplet loss for person re-identification","author":"Zeng","year":"2020"},{"issue":"4","key":"10.1016\/j.image.2025.117462_b10","doi-asserted-by":"crossref","DOI":"10.1145\/3243316","article-title":"Unsupervised person re-identification: Clustering and fine-tuning","volume":"14","author":"Fan","year":"2018","journal-title":"ACM Trans. Multimed. Comput. Commun. Appl."},{"key":"10.1016\/j.image.2025.117462_b11","first-page":"18661","article-title":"Supervised contrastive learning","volume":"vol. 33","author":"Khosla","year":"2020"},{"key":"10.1016\/j.image.2025.117462_b12","series-title":"2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"9726","article-title":"Momentum contrast for unsupervised visual representation learning","author":"He","year":"2020"},{"key":"10.1016\/j.image.2025.117462_b13","series-title":"Comparison of methods generalizing max- and average-pooling","author":"Bieder","year":"2021"},{"key":"10.1016\/j.image.2025.117462_b14","series-title":"Computer Vision \u2013 ECCV 2020: 16th European Conference, Glasgow, UK, August (2020) 23\u201328, Proceedings, Part II","first-page":"87","article-title":"Joint disentangling and adaptation for cross-domain person re-identification","author":"Zou","year":"2020"},{"key":"10.1016\/j.image.2025.117462_b15","unstructured":"Y. Ge, D. Chen, H. Li, Mutual mean-teaching: Pseudo label refinery for unsupervised domain adaptation on person re-identification, in: International Conference on Learning Representations, 2020."},{"key":"10.1016\/j.image.2025.117462_b16","series-title":"2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"12909","article-title":"Unsupervised multi-source domain adaptation for person re-identification","author":"Bai","year":"2021"},{"key":"10.1016\/j.image.2025.117462_b17","first-page":"1","article-title":"A bottom-up clustering approach to unsupervised person re-identification","volume":"vol. 2","author":"Lin","year":"2019"},{"key":"10.1016\/j.image.2025.117462_b18","series-title":"Secret: Self-consistent pseudo label refinement for unsupervised domain adaptive person re-identification","first-page":"879","author":"He","year":"2022"},{"key":"10.1016\/j.image.2025.117462_b19","series-title":"Computer Vision \u2013 ACCV 2022: 16th Asian Conference on Computer Vision, Macao, China, December (2022) 4\u20138, Proceedings, Part VI","first-page":"319","article-title":"Cluster contrast for unsupervised person re-identification","author":"Dai","year":"2023"},{"key":"10.1016\/j.image.2025.117462_b20","series-title":"2016 IEEE Conference on Computer Vision and Pattern Recognition","first-page":"770","article-title":"Deep residual learning for image recognition","author":"He","year":"2016"},{"key":"10.1016\/j.image.2025.117462_b21","series-title":"From Born-Physical To Born-Virtual: Augmenting Intelligence in Digital Libraries","first-page":"101","article-title":"Impact analysis of different effective loss functions by using deep convolutional neural network for face recognition","author":"Nguyen","year":"2022"},{"key":"10.1016\/j.image.2025.117462_b22","article-title":"Camel: Combination of asymmetrically dual representation learning with mutual data filtering and masked language modeling for text-based person retrieval","author":"Nguyen","year":"2025","journal-title":"Neurocomputing"},{"key":"10.1016\/j.image.2025.117462_b23","doi-asserted-by":"crossref","DOI":"10.1016\/j.adhoc.2019.101984","article-title":"Compact triplet loss for person re-identification in camera sensor networks","volume":"95","author":"Si","year":"2019","journal-title":"Ad Hoc Networks"},{"key":"10.1016\/j.image.2025.117462_b24","series-title":"Proceedings of the 28th ACM International Conference on Multimedia, MM \u201920","first-page":"1047","article-title":"Context-aware multi-view summarization network for image-text matching","author":"Qu","year":"2020"},{"key":"10.1016\/j.image.2025.117462_b25","series-title":"Computer Vision \u2013 ECCV 2020","first-page":"346","article-title":"Identity-guided human semantic parsing for person re-identification","author":"Zhu","year":"2020"},{"key":"10.1016\/j.image.2025.117462_b26","series-title":"2022 26th International Conference on Pattern Recognition","first-page":"2613","article-title":"Learning feature fusion for unsupervised domain adaptive person re-identification","author":"Ding","year":"2022"},{"key":"10.1016\/j.image.2025.117462_b27","doi-asserted-by":"crossref","first-page":"766","DOI":"10.1016\/j.neucom.2020.07.118","article-title":"Harmonious attention network for person re-identification via complementarity between groups and individuals","volume":"453","author":"Chen","year":"2021","journal-title":"Neurocomputing"},{"key":"10.1016\/j.image.2025.117462_b28","series-title":"2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"5363","article-title":"Dual attention matching network for context-aware feature sequence based person re-identification","author":"Si","year":"2018"},{"key":"10.1016\/j.image.2025.117462_b29","doi-asserted-by":"crossref","DOI":"10.1016\/j.image.2022.116744","article-title":"Learning global and local features using graph neural networks for person re-identification","volume":"107","author":"Zhang","year":"2022","journal-title":"Signal Process., Image Commun."},{"key":"10.1016\/j.image.2025.117462_b30","doi-asserted-by":"crossref","DOI":"10.1016\/j.image.2024.117240","article-title":"Multi-granular inter-frame relation exploration and global residual embedding for video-based person re-identification","volume":"132","author":"Zhu","year":"2025","journal-title":"Signal Process., Image Commun."},{"key":"10.1016\/j.image.2025.117462_b31","doi-asserted-by":"crossref","unstructured":"K.-H. Lee, X. Chen, G. Hua, H. Hu, X. He, Stacked cross attention for image-text matching, in: Proceedings of the European Conference on Computer Vision, (ECCV), 2018, pp. 201\u2013216.","DOI":"10.1007\/978-3-030-01225-0_13"},{"issue":"C","key":"10.1016\/j.image.2025.117462_b32","first-page":"00","article-title":"Multiview adaptive attention pooling for image\u2013text retrieval","volume":"291","author":"Ding","year":"2024","journal-title":"Know.-Based Syst."},{"key":"10.1016\/j.image.2025.117462_b33","doi-asserted-by":"crossref","first-page":"3606","DOI":"10.1109\/TIP.2022.3173163","article-title":"Cluster-guided asymmetric contrastive learning for unsupervised person re-identification","volume":"31","author":"Li","year":"2022","journal-title":"IEEE Trans. Image Process."},{"issue":"3","key":"10.1016\/j.image.2025.117462_b34","first-page":"2750","article-title":"Multi-centroid representation network for domain adaptive person re-id","volume":"36","author":"Wu","year":"2022","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"10.1016\/j.image.2025.117462_b35","series-title":"2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"5306","article-title":"Group-aware label transfer for domain adaptive person re-identification","author":"Zheng","year":"2021"},{"key":"10.1016\/j.image.2025.117462_b36","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2022.108349","article-title":"Cooperative refinement learning for domain adaptive person re-identification","volume":"242","author":"Peng","year":"2022","journal-title":"Knowl.-Based Syst."},{"key":"10.1016\/j.image.2025.117462_b37","doi-asserted-by":"crossref","unstructured":"M. Wang, B. Lai, J. Huang, X. Gong, X.-S. Hua, Camera-aware proxies for unsupervised person re-identification, in: Proceedings of the AAAI Conference on Artificial Intelligence, (AAAI), 2021.","DOI":"10.1609\/aaai.v35i4.16381"},{"key":"10.1016\/j.image.2025.117462_b38","series-title":"2022 IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"7359","article-title":"Implicit sample extension for unsupervised person re-identification","author":"Zhang","year":"2022"},{"issue":"2","key":"10.1016\/j.image.2025.117462_b39","first-page":"1527","article-title":"Reliability exploration with self-ensemble learning for domain adaptive person re-identification","volume":"36","author":"Li","year":"2022","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"10.1016\/j.image.2025.117462_b40","series-title":"Deep Learning: A Practitioner\u2019s Approach","author":"Patterson","year":"2017"},{"key":"10.1016\/j.image.2025.117462_b41","series-title":"Dynamic clustering and cluster contrastive learning for unsupervised person re-identification","author":"He","year":"2023"},{"key":"10.1016\/j.image.2025.117462_b42","series-title":"2017 IEEE International Conference on Computer Vision Workshops","first-page":"1656","article-title":"Simple triplet loss based on intra\/inter-class metric learning for face verification","author":"Ming","year":"2017"},{"key":"10.1016\/j.image.2025.117462_b43","series-title":"Proceedings of the 31st International Conference on Neural Information Processing Systems","first-page":"1195","article-title":"Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results","author":"Tarvainen","year":"2017"},{"key":"10.1016\/j.image.2025.117462_b44","series-title":"2017 IEEE Conference on Computer Vision and Pattern Recognition","first-page":"3652","article-title":"Re-ranking person re-identification with k-reciprocal encoding","author":"Zhong","year":"2017"},{"key":"10.1016\/j.image.2025.117462_b45","doi-asserted-by":"crossref","first-page":"2122","DOI":"10.1109\/TIP.2022.3152052","article-title":"Multi-source unsupervised domain adaptation via pseudo target domain","volume":"31","author":"Ren","year":"2022","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.image.2025.117462_b46","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2021.108432","article-title":"Loss function search for person re-identification","volume":"124","author":"Gu","year":"2022","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.image.2025.117462_b47","series-title":"2015 IEEE International Conference on Computer Vision","first-page":"1116","article-title":"Scalable person re-identification: A benchmark","author":"Zheng","year":"2015"},{"key":"10.1016\/j.image.2025.117462_b48","series-title":"2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"79","article-title":"Person transfer gan to bridge domain gap for person re-identification","author":"Wei","year":"2018"},{"key":"10.1016\/j.image.2025.117462_b49","series-title":"Computer Vision \u2013 ECCV 2016 Workshops","first-page":"17","article-title":"Performance measures and a data set for multi-target, multi-camera tracking","author":"Ristani","year":"2016"},{"key":"10.1016\/j.image.2025.117462_b50","article-title":"Imagenet classification with deep convolutional neural networks","volume":"vol. 25","author":"Krizhevsky","year":"2012"},{"key":"10.1016\/j.image.2025.117462_b51","series-title":"Fine-tuning cnn image retrieval with no human annotation","author":"Radenovi\u0107","year":"2018"},{"issue":"07","key":"10.1016\/j.image.2025.117462_b52","first-page":"13001","article-title":"Random erasing data augmentation","volume":"34","author":"Zhong","year":"2020","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"10.1016\/j.image.2025.117462_b53","doi-asserted-by":"crossref","first-page":"70340","DOI":"10.1109\/ACCESS.2025.3560360","article-title":"Taliu: A novel decoder and augmentation strategy for boosting tampered document image detection","volume":"13","author":"Nguyen","year":"2025","journal-title":"IEEE Access"}],"container-title":["Signal Processing: Image Communication"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0923596525002085?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0923596525002085?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T13:01:27Z","timestamp":1769518887000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0923596525002085"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3]]},"references-count":53,"alternative-id":["S0923596525002085"],"URL":"https:\/\/doi.org\/10.1016\/j.image.2025.117462","relation":{},"ISSN":["0923-5965"],"issn-type":[{"value":"0923-5965","type":"print"}],"subject":[],"published":{"date-parts":[[2026,3]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"MAPLE: Combination of multiple angles of view and enhanced pseudo-label generation for unsupervised person re-identification","name":"articletitle","label":"Article Title"},{"value":"Signal Processing: Image Communication","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.image.2025.117462","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"117462"}}