{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T14:56:05Z","timestamp":1784300165669,"version":"3.55.0"},"reference-count":85,"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":["62202227"],"award-info":[{"award-number":["62202227"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62302217"],"award-info":[{"award-number":["62302217"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004608","name":"Natural Science Foundation of Jiangsu Province","doi-asserted-by":"publisher","award":["BK20220934"],"award-info":[{"award-number":["BK20220934"]}],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004608","name":"Natural Science Foundation of Jiangsu Province","doi-asserted-by":"publisher","award":["BK20220938"],"award-info":[{"award-number":["BK20220938"]}],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004608","name":"Natural Science Foundation of Jiangsu Province","doi-asserted-by":"publisher","award":["BK20220936"],"award-info":[{"award-number":["BK20220936"]}],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Multimedia"],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/tmm.2024.3443616","type":"journal-article","created":{"date-parts":[[2024,8,15]],"date-time":"2024-08-15T17:40:41Z","timestamp":1723743641000},"page":"11139-11150","source":"Crossref","is-referenced-by-count":7,"title":["Anti-Collapse Loss for Deep Metric Learning"],"prefix":"10.1109","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4649-5937","authenticated-orcid":false,"given":"Xiruo","family":"Jiang","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0337-9410","authenticated-orcid":false,"given":"Yazhou","family":"Yao","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5526-8934","authenticated-orcid":false,"given":"Xili","family":"Dai","sequence":"additional","affiliation":[{"name":"Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7303-3231","authenticated-orcid":false,"given":"Fumin","family":"Shen","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1476-0273","authenticated-orcid":false,"given":"Liqiang","family":"Nie","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2999-2088","authenticated-orcid":false,"given":"Heng-Tao","family":"Shen","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00727"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2015.2477035"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2023.3312311"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00920"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00974"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2020.3001527"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3202571"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2019.2939711"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298682"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-021-03150-3"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2021.3096068"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2014.16"},{"key":"ref13","article-title":"In defense of the triplet loss for person re-identification","author":"Hermans","year":"2017"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01270-0_12"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2861991"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3107214"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00721"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2765836"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2023.3265159"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00265"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19830-4_34"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2023.3296629"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01505"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2023.109381"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1995.7.1.72"},{"key":"ref26","first-page":"41","article-title":"Fisher discriminant analysis with kernels","volume-title":"Proc. Neural Netw. Signal Process. IX: Proc. 1999 IEEE Signal Process. Soc. Workshop","author":"Scholkopft","year":"1999"},{"key":"ref27","first-page":"521","article-title":"Distance metric learning with application to clustering with side-information","volume-title":"Proc. Neural Inf. Process. Syst.","author":"Xing","year":"2003"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2017.2698200"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2006.100"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00208"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01246-5_45"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.47"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00330"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1002\/047174882x"},{"key":"ref35","first-page":"9422","article-title":"Learning diverse and discriminative representations via the principle of maximal coding rate reduction","volume-title":"Proc. Neural Inf. Process. Syst.","volume":"33","author":"Yu","year":"2020"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2007.1085"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.57"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33709-3_35"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2012.6247938"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2011.2133970"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2019.2919431"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2017.10.013"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2015.2477040"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-024-02106-7"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462823"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00524"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.5555\/3045118.3045167"},{"key":"ref50","first-page":"9410","article-title":"Learning intra-batch connections for deep metric learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Seidenschwarz","year":"2021"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i2.16226"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19809-0_23"},{"key":"ref53","first-page":"9095","article-title":"Simultaneous similarity-based self-distillation for deep metric learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Roth","year":"2021"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3221486"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01158"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1145\/3656047"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58583-9_23"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i2.16236"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2023.3234536"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1142\/S0218001493000339"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00516"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/ACC.2003.1243393"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/18.720554"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00655"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1016\/j.dsp.2022.103826"},{"key":"ref66","first-page":"17792","article-title":"Fewer is more: A deep graph metric learning perspective using fewer proxies","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Zhu","year":"2020"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2023.3242148"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00741"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2023.119120"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-023-08334-1"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00056"},{"key":"ref72","first-page":"8000","article-title":"Mic: Mining interclass characteristics for improved metric learning","volume-title":"Proc. IEEE Int. Conf. Comput. Vis.","author":"Roth","year":"2019"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00660"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01437"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58586-0_27"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00643"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58598-3_35"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01014"},{"key":"ref79","article-title":"The caltech-ucsd birds-200-2011 dataset","author":"Wah","year":"2011","journal-title":"California Inst. Technol."},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2013.77"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.434"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref83","first-page":"8242","article-title":"Revisiting training strategies and generalization performance in deep metric learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Roth","year":"2020"},{"key":"ref84","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298658"},{"key":"ref85","first-page":"8748","article-title":"Learning transferable visual models from natural language supervision","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Radford","year":"2021"}],"container-title":["IEEE Transactions on Multimedia"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6046\/10384483\/10637711.pdf?arnumber=10637711","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T00:27:12Z","timestamp":1732667232000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10637711\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":85,"URL":"https:\/\/doi.org\/10.1109\/tmm.2024.3443616","relation":{},"ISSN":["1520-9210","1941-0077"],"issn-type":[{"value":"1520-9210","type":"print"},{"value":"1941-0077","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]}}}