{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T13:26:27Z","timestamp":1740144387104,"version":"3.37.3"},"reference-count":82,"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"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans.Inform.Forensic Secur."],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/tifs.2024.3444319","type":"journal-article","created":{"date-parts":[[2024,8,15]],"date-time":"2024-08-15T17:31:07Z","timestamp":1723743067000},"page":"7690-7704","source":"Crossref","is-referenced-by-count":0,"title":["ROSE: Relational and Prototypical Structure Learning for Universal Domain Adaptive Hashing"],"prefix":"10.1109","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0835-8176","authenticated-orcid":false,"given":"Xinlong","family":"Yang","sequence":"first","affiliation":[{"name":"National Engineering and Research Center for Software Engineering, Peking University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5714-0149","authenticated-orcid":false,"given":"Haixin","family":"Wang","sequence":"additional","affiliation":[{"name":"National Engineering and Research Center for Software Engineering, Peking University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8138-9262","authenticated-orcid":false,"given":"Jinan","family":"Sun","sequence":"additional","affiliation":[{"name":"National Engineering and Research Center for Software Engineering, Peking University, Beijing, China"}]},{"given":"Yijia","family":"Xiao","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of California at Los Angeles, Los Angeles, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5267-3184","authenticated-orcid":false,"given":"Wei","family":"Xiang","sequence":"additional","affiliation":[{"name":"BIGO Ltd., Suntec Tower 3, Singapore"}]},{"given":"Chong","family":"Chen","sequence":"additional","affiliation":[{"name":"Terminus Group, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8232-5049","authenticated-orcid":false,"given":"Xian-Sheng","family":"Hua","sequence":"additional","affiliation":[{"name":"Terminus Group, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7987-3714","authenticated-orcid":false,"given":"Xiao","family":"Luo","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of California at Los Angeles, Los Angeles, CA, USA"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.14778\/3565816.3565819"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2023.3290790"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2022.3207897"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2022.3192716"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00960"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01174"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3071127"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2020.3024593"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298862"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2699960"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.2975798"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.227"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2827036"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2019.2943902"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/344"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/3209978.3209999"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/3474085.3475526"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3123266.3123403"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01237-3_9"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.2964173"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2880750"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3119965"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00963"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i6.20574"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00887"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/3532624"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3114089"},{"article-title":"Guided similarity separation for image retrieval","volume-title":"Proc. NeurIPS","author":"Liu","key":"ref28"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01334"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2022.3161149"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00306"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-019-01166-4"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i3.16296"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00386"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01187"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/133"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00289"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/125"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2022.3222624"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00315"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2020\/115"},{"key":"ref42","first-page":"24286","article-title":"One loss for all: Deep hashing with a single cosine similarity based learning objective","volume-title":"Proc. NeurIPS","author":"Hoe"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01609"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.572"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01818"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3128560"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19827-4_37"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00283"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00642"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1145\/3581783.3612225"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/WACV57701.2024.00018"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3547937"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2021.3064377"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1145\/3581783.3613811"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00254"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00884"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01566"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01818"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3091944"},{"key":"ref60","article-title":"Rank-based decomposable losses in machine learning: A survey","author":"Hu","year":"2022","journal-title":"arXiv:2207.08768"},{"key":"ref61","article-title":"Noisy feature mixup","author":"Lim","year":"2021","journal-title":"arXiv:2110.02180"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539248"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01019"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"ref65","first-page":"1597","article-title":"A simple framework for contrastive learning of visual representations","volume-title":"Proc. ICML","author":"Chen"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2023.3280859"},{"key":"ref67","first-page":"596","article-title":"FixMatch: Simplifying semi-supervised learning with consistency and confidence","volume-title":"Proc. NeurIPS","author":"Sohn"},{"key":"ref68","first-page":"9912","article-title":"Unsupervised learning of visual features by contrasting cluster assignments","volume-title":"Proc. NeurIPS","author":"Caron"},{"article-title":"Self-labelling via simultaneous clustering and representation learning","volume-title":"Proc. ICLR","author":"Asano","key":"ref69"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00527"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3548403"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-15561-1_16"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2018.00271"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01521"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3161600"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1145\/3474085.3475498"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449825"},{"key":"ref78","article-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2014","journal-title":"arXiv:1409.1556"},{"key":"ref79","first-page":"26991","article-title":"Make the U in UDA matter: Invariant consistency learning for unsupervised domain adaptation","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"36","author":"Yue"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2023.3242777"},{"key":"ref81","article-title":"Representation learning with contrastive predictive coding","author":"van den Oord","year":"2018","journal-title":"arXiv:1807.03748"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.1145\/3240508.3240543"}],"container-title":["IEEE Transactions on Information Forensics and Security"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10206\/10319981\/10637714.pdf?arnumber=10637714","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,2]],"date-time":"2024-09-02T04:07:27Z","timestamp":1725250047000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10637714\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":82,"URL":"https:\/\/doi.org\/10.1109\/tifs.2024.3444319","relation":{},"ISSN":["1556-6013","1556-6021"],"issn-type":[{"type":"print","value":"1556-6013"},{"type":"electronic","value":"1556-6021"}],"subject":[],"published":{"date-parts":[[2024]]}}}