{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T10:08:46Z","timestamp":1777889326686,"version":"3.51.4"},"reference-count":57,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,10,19]],"date-time":"2025-10-19T00:00:00Z","timestamp":1760832000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,10,19]],"date-time":"2025-10-19T00:00:00Z","timestamp":1760832000000},"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":["82172033,U19B2031,61971369,52105126,82272071,62271430"],"award-info":[{"award-number":["82172033,U19B2031,61971369,52105126,82272071,62271430"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,19]]},"DOI":"10.1109\/iccv51701.2025.00035","type":"proceedings-article","created":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T19:45:49Z","timestamp":1777491949000},"page":"297-307","source":"Crossref","is-referenced-by-count":0,"title":["Dissecting Generalized Category Discovery: Multiplex Consensus under Self-Deconstruction"],"prefix":"10.1109","author":[{"given":"Luyao","family":"Tang","sequence":"first","affiliation":[{"name":"Ministry of Education of China, Xiamen University,Key Laboratory of Multimedia Trusted Perception and Efficient Computing"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kunze","family":"Huang","sequence":"additional","affiliation":[{"name":"Ministry of Education of China, Xiamen University,Key Laboratory of Multimedia Trusted Perception and Efficient Computing"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chaoqi","family":"Chen","sequence":"additional","affiliation":[{"name":"Shenzhen University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuxuan","family":"Yuan","sequence":"additional","affiliation":[{"name":"Ministry of Education of China, Xiamen University,Key Laboratory of Multimedia Trusted Perception and Efficient Computing"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chenxin","family":"Li","sequence":"additional","affiliation":[{"name":"The Chinese University of Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaotong","family":"Tu","sequence":"additional","affiliation":[{"name":"Ministry of Education of China, Xiamen University,Key Laboratory of Multimedia Trusted Perception and Efficient Computing"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinghao","family":"Ding","sequence":"additional","affiliation":[{"name":"Ministry of Education of China, Xiamen University,Key Laboratory of Multimedia Trusted Perception and Efficient Computing"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yue","family":"Huang","sequence":"additional","affiliation":[{"name":"Ministry of Education of China, Xiamen University,Key Laboratory of Multimedia Trusted Perception and Efficient Computing"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1038\/npjscilearn.2016.4"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.52202\/075280-1424"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/WACV57701.2024.00210"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.physrep.2014.02.005"},{"key":"ref5","author":"Cao","year":"2021","journal-title":"Open-world semi-supervised learning"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01597"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00951"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1126\/science.7134969"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00166"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr52733.2024.02179"},{"key":"ref11","article-title":"Empirical evaluation of gated recurrent neural networks on sequence modeling","author":"Chung","year":"2014","journal-title":"arXiv preprint"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/MWSCAS.2017.8053243"},{"key":"ref13","article-title":"Oxford English Dictionary","volume":"3","year":"1989","journal-title":"Oxford english dictionary. Simpson, Ja & Weiner, Esc"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.52202\/068431-2098"},{"key":"ref15","article-title":"Xcon: Learning with experts for fine-grained category discovery","author":"Fei","year":"2022","journal-title":"arXiv preprint"},{"key":"ref16","article-title":"Learning visual attributes","volume":"20","author":"Ferrari","year":"2007","journal-title":"Advances in neural information processing systems"},{"key":"ref17","article-title":"Imagenet-trained cnns are biased towards texture; increasing shape bias improves accuracy and robustness","author":"Geirhos","year":"2018","journal-title":"arXiv preprint"},{"key":"ref18","article-title":"Imagenet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness","volume-title":"International Conference on Learning Representations","author":"Geirhos","year":"2019"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-020-00257-z"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177704250"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01840"},{"key":"ref22","first-page":"5338","article-title":"Concept bottleneck models","volume-title":"International conference on machine learning","author":"Wei Koh","year":"2020"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2013.77"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.brainres.2010.11.080"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.cortex.2010.04.008"},{"key":"ref26","author":"Krizhevsky","year":"2009","journal-title":"Learning multiple layers of features from tiny images"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.5555\/2999134.2999257"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01667"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.52202\/075280-3141"},{"key":"ref30","first-page":"11525","article-title":"Objectcentric learning with slot attention","volume":"33","author":"Locatello","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01598"},{"key":"ref32","article-title":"Fine-grained visual classification of aircraft","author":"Maji","year":"2013","journal-title":"arXiv preprint"},{"key":"ref33","article-title":"Representation learning with contrastive predictive coding","author":"van den Oord","year":"2018","journal-title":"arXiv preprint"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/WACV57701.2024.00260"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1007\/978-94-017-2012-0_7"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00732"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.02715"},{"key":"ref38","article-title":"Learn to categorize or categorize to learn? self-coding for generalized category discovery","volume":"36","author":"Rastegar","year":"2024","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-72897-6_25"},{"key":"ref40","article-title":"Imagenet-21k pretraining for the masses","author":"Ridnik","year":"2021","journal-title":"arXiv preprint"},{"key":"ref41","article-title":"Bridging the gap to real-world object-centric learning","author":"Seitzer","year":"2022","journal-title":"arXiv preprint"},{"key":"ref42","article-title":"Bridging the gap to real-world object-centric learning","volume-title":"The Eleventh International Conference on Learning Representations","author":"Seitzer","year":"2023"},{"key":"ref43","article-title":"The herbarium challenge 2019 dataset","author":"Chuan Tan","year":"2019","journal-title":"arXiv preprint"},{"key":"ref44","article-title":"Neural discrete representation learning","volume":"30","author":"Van Den Oord","year":"2017","journal-title":"Advances in neural information processing systems"},{"issue":"86","key":"ref45","first-page":"2579","article-title":"Visualizing data using t-sne","volume":"9","author":"van der Maaten","year":"2008","journal-title":"Journal of Machine Learning Research"},{"key":"ref46","article-title":"Attention is all you need","author":"Vaswani","year":"2017","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref47","author":"Vaze","year":"2021","journal-title":"Open-set recognition: A good closed-set classifier is all you need"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00734"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.52202\/075280-0876"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/ICTAI.2010.11"},{"key":"ref51","author":"Wah","year":"2011","journal-title":"The caltech-ucsd birds-200\u20132011 dataset"},{"key":"ref52","article-title":"Sptnet: An efficient alternative framework for generalized category discovery with spatial prompt tuning","author":"Wang","year":"2024","journal-title":"arXiv preprint"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01521"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1016\/0305-0548(90)90031-2"},{"key":"ref55","article-title":"Concept embedding models","volume-title":"NeurIPS 2022\u201336th Conference on Neural Information Processing Systems","author":"Espinosa Zarlenga","year":"2022"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00339"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/iccv51070.2023.01524"}],"event":{"name":"2025 IEEE\/CVF International Conference on Computer Vision (ICCV)","location":"Honolulu, HI, USA","start":{"date-parts":[[2025,10,19]]},"end":{"date-parts":[[2025,10,25]]}},"container-title":["2025 IEEE\/CVF International Conference on Computer Vision (ICCV)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11443115\/11443287\/11444874.pdf?arnumber=11444874","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T05:09:19Z","timestamp":1777612159000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11444874\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,19]]},"references-count":57,"URL":"https:\/\/doi.org\/10.1109\/iccv51701.2025.00035","relation":{},"subject":[],"published":{"date-parts":[[2025,10,19]]}}}