{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T19:41:45Z","timestamp":1785958905718,"version":"3.56.0"},"reference-count":71,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"National Key Research and Development Plan of China","award":["2020AAA0108902"],"award-info":[{"award-number":["2020AAA0108902"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62206288"],"award-info":[{"award-number":["62206288"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Intell. Veh."],"published-print":{"date-parts":[[2024,1]]},"DOI":"10.1109\/tiv.2023.3337795","type":"journal-article","created":{"date-parts":[[2023,11,30]],"date-time":"2023-11-30T19:24:53Z","timestamp":1701372293000},"page":"1589-1601","source":"Crossref","is-referenced-by-count":15,"title":["Multi-Prototype Guided Source-Free Domain Adaptive Object Detection for Autonomous Driving"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-3053-8637","authenticated-orcid":false,"given":"Siqi","family":"Zhang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6240-5300","authenticated-orcid":false,"given":"Lu","family":"Zhang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guangsen","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pengcheng","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2148-1846","authenticated-orcid":false,"given":"Zhiyong","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","article-title":"Benchmarking robustness in object detection: Autonomous driving when winter is coming","author":"Michaelis","year":"2019"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2021.3096854"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/tpami.2016.2577031"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.l007\/978-3-319-46448-0_2"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.322"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00972"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00352"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00712"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01274"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01174"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58621-8_24"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01172"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00408"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2021.3091620"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00743"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/tiv.2023.3308896"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-30111-7_21"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2022.3197818"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2022.3165353"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/3581783.3613116"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i10.17029"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2021.3111034"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00785"},{"key":"ref24","first-page":"3635","article-title":"Model adaptation: Historical contrastive learning for unsupervised domain adaptation without source data","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Huang","year":"2021"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00343"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-022-01728-z"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3060446"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.108436"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2021.3104835"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP49357.2023.10096635"},{"key":"ref31","first-page":"26007","article-title":"Semi-supervised semantic segmentation with prototype-based consistency regularization","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Xu","year":"2022"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19830-4_10"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2023.126265"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00935"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.244"},{"key":"ref36","first-page":"1195","article-title":"Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Tarvainen","year":"2017"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2023.3235367"},{"key":"ref38","first-page":"6028","article-title":"Do we really need to access the source data? Source hypothesis transfer for unsupervised domain adaptation","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Liang","year":"2020"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00966"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00888"},{"key":"ref41","first-page":"29393","article-title":"Exploiting the intrinsic neighborhood structure for source-free domain adaptation","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Yang","year":"2021"},{"key":"ref42","first-page":"5802","article-title":"Attracting and dispersing: A simple approach for source-free domain adaptation","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Yang","year":"2022"},{"key":"ref43","first-page":"11710","article-title":"Balancing discriminability and transferability for source-free domain adaptation","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Kundu","year":"2022"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00127"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00696"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2022.102457"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2022.3179021"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-022-04364-9"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i1.25119"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2023.3247103"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2022.3175605"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3222871"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2022.3163458"},{"key":"ref54","article-title":"On mutual information maximization for representation learning","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Tschannen","year":"2019"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00127"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2023.3237740"},{"key":"ref57","article-title":"Self-ensembling for visual domain adaptation","volume-title":"Proc. Int. Conf. Learn. Representations","author":"French","year":"2018"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1016\/0377-0427(87)90125-7"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.2307\/2346830"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177729694"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.5555\/3524938.3525087"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.350"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-018-1072-8"},{"key":"ref64","first-page":"2636","article-title":"Bdd100k: A diverse driving dataset for heterogeneous multitask learning","volume-title":"Proc. IEEE\/CVF Conf. Comput. Vis. Pattern Recognit.","author":"Fisher","year":"2020"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2017.7989092"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1177\/0278364913491297"},{"key":"ref67","article-title":"Very deep convolutional networks for large-scale image recognition","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Simonyan","year":"2015"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-7908-2604-3_16"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.5555\/3454287.3455008"},{"issue":"11","key":"ref71","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"Maaten","year":"2008","journal-title":"J. Mach. Learn. Res."}],"container-title":["IEEE Transactions on Intelligent Vehicles"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7274857\/10443740\/10336548.pdf?arnumber=10336548","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,27]],"date-time":"2025-06-27T17:47:38Z","timestamp":1751046458000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10336548\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1]]},"references-count":71,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tiv.2023.3337795","relation":{},"ISSN":["2379-8904","2379-8858"],"issn-type":[{"value":"2379-8904","type":"electronic"},{"value":"2379-8858","type":"print"}],"subject":[],"published":{"date-parts":[[2024,1]]}}}