{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,3]],"date-time":"2025-12-03T19:03:40Z","timestamp":1764788620165,"version":"3.46.0"},"reference-count":85,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":["62376196","62036012","U23A20387","62106262","62202331","62206200","62276118"],"award-info":[{"award-number":["62376196","62036012","U23A20387","62106262","62202331","62206200","62276118"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"Tianjin Natural Science Foundation","doi-asserted-by":"publisher","award":["22JCYBJC00030","24JCJQJC00190"],"award-info":[{"award-number":["22JCYBJC00030","24JCJQJC00190"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Beijing Natural Science Foundation","award":["L252032"],"award-info":[{"award-number":["L252032"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Image Process."],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/tip.2025.3628454","type":"journal-article","created":{"date-parts":[[2025,11,10]],"date-time":"2025-11-10T18:50:58Z","timestamp":1762800658000},"page":"7627-7641","source":"Crossref","is-referenced-by-count":0,"title":["Dual Uncertainty-Aware Correspondence Adapting and Retaining for Continual Composed Image Retrieval"],"prefix":"10.1109","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5663-3358","authenticated-orcid":false,"given":"Haoliang","family":"Zhou","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, Tianjin University of Technology, Tianjin, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8153-9977","authenticated-orcid":false,"given":"Feifei","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering and the Key Laboratory of Computer Vision and System, Ministry of Education, Tianjin University of Technology, Tianjin, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8343-9665","authenticated-orcid":false,"given":"Changsheng","family":"Xu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-025-02393-8"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2025.3555485"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2024.3367416"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00660"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/WACV57701.2024.00565"},{"key":"ref6","first-page":"1","article-title":"Sentence-level prompts benefit composed image retrieval","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Bai"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2023.3235495"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i2.27885"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2023.3299791"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2022.3204213"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462967"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3478642"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2024.3359062"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/iros.1994.407413"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01219-9_9"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3213473"},{"key":"ref17","first-page":"35607","article-title":"Rethinking momentum knowledge distillation in online continual learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Michel"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2773081"},{"key":"ref19","first-page":"1","article-title":"Continual learning with tiny episodic memories","volume-title":"Proc. Workshop Multi-Task Lifelong Reinforcement Learn.","author":"Chaudhry"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.02204"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01065"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-025-02398-3"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.02034"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/3581783.3612207"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW53098.2021.00402"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/3664647.3680591"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00726"},{"key":"ref29","first-page":"29406","article-title":"Learning with noisy correspondence for cross-modal matching","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"34","author":"Huang"},{"key":"ref30","first-page":"24829","article-title":"Cross-modal active complementary learning with self-refining correspondence","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Qin"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2023.3247939"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2024.3374221"},{"key":"ref33","first-page":"22379","article-title":"AFEC: Active forgetting of negative transfer in continual learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Wang"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.587"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01620"},{"key":"ref36","first-page":"3179","article-title":"Evidential deep learning to quantify classification uncertainty","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"31","author":"\u015eensoy"},{"volume-title":"Subjective Logic: A Formalism for Reasoning Under Uncertainty","year":"2018","author":"Jsang","key":"ref37"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3547922"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/3664647.3681629"},{"key":"ref40","first-page":"1","article-title":"An image is worth 16\u00d716 words: Transformers for image recognition at scale","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Dosovitskiy"},{"key":"ref41","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","author":"Devlin","year":"2018","journal-title":"arXiv:1810.04805"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3138302"},{"key":"ref43","first-page":"8748","article-title":"Learning transferable visual models from natural language supervision","volume-title":"Proc. Int. Conf. Mach. Learn.","volume":"139","author":"Radford"},{"key":"ref44","first-page":"12888","article-title":"Bootstrapping language-image pre-training for unified vision-language understanding and generation","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Li"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW56347.2022.00543"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00262"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i4.28081"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2024.3367329"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2024.3371349"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1611835114"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01252-6_33"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/WACV45572.2020.9093365"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.10.021"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00092"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00303"},{"key":"ref56","first-page":"4548","article-title":"Overcoming catastrophic forgetting with hard attention to the task","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Serra"},{"key":"ref57","first-page":"3925","article-title":"Learn to grow: A continual structure learning framework for overcoming catastrophic forgetting","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Li"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01831"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00276"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i1.25208"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2023.3310336"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1145\/3581783.3611919"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2020.107675"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3152990"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3053577"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3151979"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2023.3347722"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3548091"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-16431-6_64"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01310"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1145\/3581783.3611824"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2022.3222623"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2024.3522807"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i4.28101"},{"key":"ref75","first-page":"1","article-title":"Rethinking score distilling sampling for 3D editing and generation","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Miao"},{"key":"ref76","first-page":"1","article-title":"Composed image retrieval with text feedback via multi-grained uncertainty regularization","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Chen"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2024.3401006"},{"key":"ref78","first-page":"1877","article-title":"Language models are few-shot learners","volume-title":"Proc. NIPS","author":"Brown"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01115"},{"key":"ref80","first-page":"1","article-title":"Dialog-based interactive image retrieval","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Guo"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00677"},{"key":"ref82","first-page":"9694","article-title":"Align before fuse: Vision and language representation learning with momentum distillation","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Li"},{"key":"ref83","doi-asserted-by":"publisher","DOI":"10.1515\/9780691214696"},{"key":"ref84","first-page":"18237","article-title":"Improving model calibration with accuracy versus uncertainty optimization","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Krishnan"},{"key":"ref85","first-page":"3987","article-title":"Continual learning through synaptic intelligence","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Zenke"}],"container-title":["IEEE Transactions on Image Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/83\/10795784\/11237027.pdf?arnumber=11237027","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,3]],"date-time":"2025-12-03T18:44:58Z","timestamp":1764787498000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11237027\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":85,"URL":"https:\/\/doi.org\/10.1109\/tip.2025.3628454","relation":{},"ISSN":["1057-7149","1941-0042"],"issn-type":[{"type":"print","value":"1057-7149"},{"type":"electronic","value":"1941-0042"}],"subject":[],"published":{"date-parts":[[2025]]}}}