{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T06:48:08Z","timestamp":1781592488817,"version":"3.54.5"},"reference-count":85,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T00:00:00Z","timestamp":1706745600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T00:00:00Z","timestamp":1706745600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T00:00:00Z","timestamp":1706745600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62076262"],"award-info":[{"award-number":["62076262"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Intell. Transport. Syst."],"published-print":{"date-parts":[[2024,2]]},"DOI":"10.1109\/tits.2023.3314453","type":"journal-article","created":{"date-parts":[[2023,9,21]],"date-time":"2023-09-21T17:49:01Z","timestamp":1695318541000},"page":"1953-1965","source":"Crossref","is-referenced-by-count":29,"title":["Spatial and Temporal Dual-Attention for Unsupervised Person Re-Identification"],"prefix":"10.1109","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-2204-8668","authenticated-orcid":false,"given":"Qiaolin","family":"He","sequence":"first","affiliation":[{"name":"School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-9445-8052","authenticated-orcid":false,"given":"Zihan","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5584-1785","authenticated-orcid":false,"given":"Zhijie","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4884-323X","authenticated-orcid":false,"given":"Haifeng","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3013379"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2023.3262130"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2020.3025387"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2021.3137954"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.266"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2019.00190"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58571-6_43"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2022.3157463"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01225-0_30"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/WACV45572.2020.9093541"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3243316"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2893066"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00702"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00621"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01367"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.443"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00110"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00225"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00069"},{"key":"ref20","article-title":"Multi-task mid-level feature alignment network for unsupervised cross-dataset person re-identification","volume-title":"Proc. 29th Brit. Mach. Vis. Conf. (BMVC)","author":"Lin"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33018738"},{"key":"ref22","first-page":"11309","article-title":"Self-paced contrastive learning with hybrid memory for domain adaptive object re-ID","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Ge"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00344"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01469"},{"issue":"34","key":"ref25","first-page":"226","article-title":"A density-based algorithm for discovering clusters in large spatial databases with noise","volume-title":"Proc. KDD","volume":"96","author":"Ester"},{"key":"ref26","first-page":"281","article-title":"Classification and analysis of multivariate observations","volume-title":"Proc. 5th Berkeley Symp. Math. Statist. Probab.","author":"MacQueen"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298682"},{"key":"ref28","article-title":"In defense of the triplet loss for person re-identification","author":"Hermans","year":"2017","journal-title":"arXiv:1703.07737"},{"key":"ref29","article-title":"Representation learning with contrastive predictive coding","author":"van den Oord","year":"2018","journal-title":"arXiv:1807.03748"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01099"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00904"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"key":"ref33","article-title":"Mutual mean-teaching: Pseudo label refinery for unsupervised domain adaptation on person re-identification","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Ge"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58571-6_35"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00716"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-26351-4_20"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00813"},{"key":"ref38","article-title":"Residual non-local attention networks for image restoration","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Zhang"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3152527"},{"key":"ref40","first-page":"961","article-title":"Decoupling \u2018when to update\u2019 from \u2018how to update","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"30","author":"Malach"},{"key":"ref41","first-page":"2304","article-title":"MentorNet: Learning data-driven curriculum for very deep neural networks on corrupted labels","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Jiang"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01374"},{"key":"ref43","first-page":"5739","article-title":"Learning with bad training data via iterative trimmed loss minimization","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Shen"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00041"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.168"},{"key":"ref46","article-title":"Training convolutional networks with noisy labels","volume-title":"Proc. 3rd Int. Conf. Learn. Represent. (ICLR)","author":"Sukhbaatar"},{"key":"ref47","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"Srivastava","year":"2014","journal-title":"J. Mach. Learn. Res."},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2016.7472164"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298885"},{"key":"ref50","first-page":"5836","article-title":"Masking: A new perspective of noisy supervision","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"31","author":"Han"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2877939"},{"key":"ref52","first-page":"3763","article-title":"Robust inference via generative classifiers for handling noisy labels","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Lee"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.10894"},{"key":"ref54","article-title":"Generalized cross entropy loss for training deep neural networks with noisy labels","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"31","author":"Zhang"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00041"},{"key":"ref56","article-title":"Curriculum loss: Robust learning and generalization against label corruption","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Lyu"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-019-0197-0"},{"key":"ref58","first-page":"950","article-title":"A simple weight decay can improve generalization","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"4","author":"Krogh"},{"key":"ref59","first-page":"448","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Ioffe"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01150"},{"key":"ref61","article-title":"Training deep neural networks on noisy labels with bootstrapping","volume-title":"Proc. ICLR Workshop","author":"Reed"},{"key":"ref62","first-page":"312","article-title":"Unsupervised label noise modeling and loss correction","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Arazo"},{"key":"ref63","first-page":"19365","article-title":"Self-adaptive training: Beyond empirical risk minimization","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Huang"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i13.17363"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00393"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00345"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2022.3224233"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/IC-NIDC54101.2021.9660560"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58586-0_29"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00204"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01175"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2021.3103961"},{"key":"ref74","first-page":"315","article-title":"Deep sparse rectifier neural networks","volume-title":"Proc. 14th Int. Conf. Artif. Intell. Statist.","author":"Glorot"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.133"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00016"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46475-6_53"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1145\/3159171"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.389"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.7000"},{"key":"ref83","article-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2014","journal-title":"arXiv:1412.6980"},{"issue":"11","key":"ref84","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"Van der Maaten","year":"2008","journal-title":"J. Mach. Learn. Res."},{"key":"ref85","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.74"}],"container-title":["IEEE Transactions on Intelligent Transportation Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6979\/10419116\/10260257.pdf?arnumber=10260257","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,11]],"date-time":"2024-12-11T02:39:35Z","timestamp":1733884775000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10260257\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,2]]},"references-count":85,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/tits.2023.3314453","relation":{},"ISSN":["1524-9050","1558-0016"],"issn-type":[{"value":"1524-9050","type":"print"},{"value":"1558-0016","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,2]]}}}