{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T04:09:59Z","timestamp":1785211799076,"version":"3.55.0"},"reference-count":78,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","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":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62293482"],"award-info":[{"award-number":["62293482"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Basic Research Project of Hetao Shenzhen-HK Science and Technology Cooperation Zone","award":["HZQB-KCZYZ-2021067"],"award-info":[{"award-number":["HZQB-KCZYZ-2021067"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62322608"],"award-info":[{"award-number":["62322608"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["22lgqb25"],"award-info":[{"award-number":["22lgqb25"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shenzhen Science and Technology Program","award":["JCYJ20220530141211024"],"award-info":[{"award-number":["JCYJ20220530141211024"]}]},{"name":"Open Project Program of the Key Laboratory of Artificial Intelligence for Perception and Understanding, Liaoning Province","award":["20230003"],"award-info":[{"award-number":["20230003"]}]},{"name":"National Key Research and Development Program of China","award":["2018YFB1800800"],"award-info":[{"award-number":["2018YFB1800800"]}]},{"DOI":"10.13039\/501100001809","name":"Shenzhen Outstanding Talents Training Fund","doi-asserted-by":"publisher","award":["202002"],"award-info":[{"award-number":["202002"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Image Process."],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/tip.2024.3451928","type":"journal-article","created":{"date-parts":[[2024,9,5]],"date-time":"2024-09-05T18:50:48Z","timestamp":1725562248000},"page":"5525-5537","source":"Crossref","is-referenced-by-count":7,"title":["Contrastive Open-Set Active Learning-Based Sample Selection for Image Classification"],"prefix":"10.1109","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5920-1390","authenticated-orcid":false,"given":"Zizheng","family":"Yan","sequence":"first","affiliation":[{"name":"Shenzhen Future Network of Intelligence Institute, the School of Science and Engineering, and the Guangdong Provincial Key Laboratory of Future Networks of Intelligence, Chinese University of Hong Kong at Shenzhen, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Delian","family":"Ruan","sequence":"additional","affiliation":[{"name":"Meituan, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-9725-0606","authenticated-orcid":false,"given":"Yushuang","family":"Wu","sequence":"additional","affiliation":[{"name":"Shenzhen Future Network of Intelligence Institute, the School of Science and Engineering, and the Guangdong Provincial Key Laboratory of Future Networks of Intelligence, Chinese University of Hong Kong at Shenzhen, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8395-1463","authenticated-orcid":false,"given":"Junshi","family":"Huang","sequence":"additional","affiliation":[{"name":"Meituan, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1979-1167","authenticated-orcid":false,"given":"Zhenhua","family":"Chai","sequence":"additional","affiliation":[{"name":"Meituan, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0162-3296","authenticated-orcid":false,"given":"Xiaoguang","family":"Han","sequence":"additional","affiliation":[{"name":"Shenzhen Future Network of Intelligence Institute, the School of Science and Engineering, and the Guangdong Provincial Key Laboratory of Future Networks of Intelligence, Chinese University of Hong Kong at Shenzhen, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2608-775X","authenticated-orcid":false,"given":"Shuguang","family":"Cui","sequence":"additional","affiliation":[{"name":"Shenzhen Future Network of Intelligence Institute, the School of Science and Engineering, and the Guangdong Provincial Key Laboratory of Future Networks of Intelligence, Chinese University of Hong Kong at Shenzhen, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4805-0926","authenticated-orcid":false,"given":"Guanbin","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Research Institute of Sun Yat-sen University in Shenzhen, Sun Yat-sen University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46493-0_38"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/2959100.2959190"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref4","article-title":"Active learning literature survey","author":"Settles","year":"1648"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3472291"},{"key":"ref6","first-page":"1183","article-title":"Deep Bayesian active learning with image data","volume-title":"Proc. ICML","author":"Gal"},{"key":"ref7","article-title":"Deep batch active learning by diverse, uncertain gradient lower bounds","author":"Ash","year":"2019","journal-title":"arXiv:1906.03671"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01192"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2016.2589879"},{"key":"ref10","article-title":"Active learning for convolutional neural networks: A core-set approach","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Sener"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00018"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00607"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58517-4_9"},{"key":"ref14","first-page":"11933","article-title":"Batch active learning at scale","volume-title":"Proc. NeurIPS","volume":"34","author":"Citovsky"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58607-2_30"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00946"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00529"},{"key":"ref18","article-title":"Active learning on a budget: Opposite strategies suit high and low budgets","author":"Hacohen","year":"2022","journal-title":"arXiv:2202.02794"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00014"},{"key":"ref20","article-title":"Open-set recognition: A good closed-set classifier is all you need?","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Vaze"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/B978-1-55860-335-6.50026-X"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/11871842_40"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206627"},{"key":"ref24","article-title":"Adversarial active learning for deep networks: A margin based approach","author":"Ducoffe","year":"2018","journal-title":"arXiv:1802.09841"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00914"},{"key":"ref26","article-title":"Bayesian active learning for classification and preference learning","author":"Houlsby","year":"2011","journal-title":"arXiv:1112.5745"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2016.90"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i8.20834"},{"key":"ref29","article-title":"Generative adversarial active learning","author":"Zhu","year":"2017","journal-title":"arXiv:1702.07956"},{"key":"ref30","article-title":"Diverse mini-batch active learning","author":"Zhdanov","year":"2019","journal-title":"arXiv:1901.05954"},{"key":"ref31","article-title":"Deep active learning over the long tail","author":"Geifman","year":"2017","journal-title":"arXiv:1711.00941"},{"key":"ref32","article-title":"Batch active learning using determinantal point processes","author":"B\u0131y\u0131k","year":"2019","journal-title":"arXiv:1906.07975"},{"key":"ref33","article-title":"Discriminative active learning","author":"Gissin","year":"2019","journal-title":"arXiv:1907.06347"},{"key":"ref34","first-page":"1308","article-title":"Deep active learning: Unified and principled method for query and training","volume-title":"Proc. AISTATS","author":"Shui"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1312.6114"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2017.67"},{"key":"ref37","article-title":"Multiple-criteria based active learning with fixed-size determinantal point processes","author":"Zhan","year":"2021","journal-title":"arXiv:2107.01622"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.48550\/arxiv.1710.09412"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2014.2321392"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.173"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01231-1_38"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.5244\/C.31.42"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00085"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00414"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00241"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01349"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58580-8_30"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3106743"},{"key":"ref49","first-page":"25956","article-title":"OpenMatch: Open-set semi-supervised learning with open-set consistency regularization","volume-title":"Proc. NeurIPS","volume":"34","author":"Saito"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01472"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00820"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/WACV57701.2024.00235"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19821-2_22"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW56347.2022.00413"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00703"},{"key":"ref56","article-title":"Few-shot object recognition based on three-way decision and active learning","volume":"37","author":"Li","year":"2022","journal-title":"Vis. Comput."},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19806-9_22"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00882"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01238"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00849"},{"key":"ref61","first-page":"22982","article-title":"Novel visual category discovery with dual ranking statistics and mutual knowledge distillation","volume-title":"Proc. NeurIPS","volume":"34","author":"Zhao"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00734"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00915"},{"key":"ref64","article-title":"Meta discovery: Learning to discover novel classes given very limited data","author":"Chi","year":"2021","journal-title":"arXiv:2102.04002"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00880"},{"key":"ref66","first-page":"18685","article-title":"Similar: Submodular information measures based active learning in realistic scenarios","volume-title":"Proc. NeurIPS","volume":"34","author":"Kothawade"},{"key":"ref67","first-page":"31416","article-title":"Meta-query-net: Resolving purity-informativeness dilemma in open-set active learning","volume-title":"Proc. NeurIPS","volume":"35","author":"Park"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00732"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01521"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00166"},{"key":"ref71","first-page":"1597","article-title":"A simple framework for contrastive learning of visual representations","volume-title":"Proc. ICML","author":"Chen"},{"key":"ref72","volume-title":"Learning multiple layers of features from tiny images","author":"Krizhevsky","year":"2009"},{"key":"ref73","volume-title":"Tiny ImageNet visual recognition challenge","author":"Le","year":"2015"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref75","first-page":"9912","article-title":"Unsupervised learning of visual features by contrasting cluster assignments","volume-title":"Proc. NeuIPS","author":"Caron"},{"issue":"11","key":"ref76","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":"ref77","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.11174"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1109\/ICVGIP.2008.47"}],"container-title":["IEEE Transactions on Image Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/83\/10346232\/10667005.pdf?arnumber=10667005","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,7]],"date-time":"2024-10-07T17:54:07Z","timestamp":1728323647000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10667005\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":78,"URL":"https:\/\/doi.org\/10.1109\/tip.2024.3451928","relation":{},"ISSN":["1057-7149","1941-0042"],"issn-type":[{"value":"1057-7149","type":"print"},{"value":"1941-0042","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]}}}