{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T11:21:11Z","timestamp":1783509671992,"version":"3.55.0"},"reference-count":54,"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\/501100005089","name":"Beijing Natural Science Foundation","doi-asserted-by":"publisher","award":["4234086"],"award-info":[{"award-number":["4234086"]}],"id":[{"id":"10.13039\/501100005089","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62192782"],"award-info":[{"award-number":["62192782"]}],"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":[[2025]]},"DOI":"10.1109\/tip.2025.3558442","type":"journal-article","created":{"date-parts":[[2025,4,11]],"date-time":"2025-04-11T14:07:35Z","timestamp":1744380455000},"page":"4751-4766","source":"Crossref","is-referenced-by-count":3,"title":["Content-Decoupled Contrastive Learning-Based Implicit Degradation Modeling for Blind Image Super-Resolution"],"prefix":"10.1109","volume":"34","author":[{"given":"Jiang","family":"Yuan","sequence":"first","affiliation":[{"name":"State Key Laboratory of Multimodal Artificial Intelligence Systems, CASIA, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ji","family":"Ma","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Multimodal Artificial Intelligence Systems, CASIA, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5596-1795","authenticated-orcid":false,"given":"Bo","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Multimodal Artificial Intelligence Systems, CASIA, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9237-8825","authenticated-orcid":false,"given":"Weiming","family":"Hu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Multimodal Artificial Intelligence Systems, CASIA, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2439281"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01234-2_18"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.151"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2023.3348293"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2024.3368960"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.19"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.207"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00344"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00170"},{"key":"ref10","first-page":"5632","article-title":"Unfolding the alternating optimization for blind super resolution","volume-title":"Proc. NeurIPS","author":"Luo"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01044"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2023.3283922"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2021.3139209"},{"key":"ref14","first-page":"195","article-title":"Fuzzy logic: Between human reasoning and artificial intelligence","volume-title":"J. Mind Behav.","volume":"13","author":"Dernoncourt","year":"1992"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.108984"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.150"},{"issue":"86","key":"ref17","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"Van der Maaten","year":"2008","journal-title":"JMLR"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.5555\/3495724.3497510"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19809-0_17"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2024.3385276"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2022.3160072"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.182"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00745"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW54120.2021.00210"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01251"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01712"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"ref30","first-page":"894","article-title":"Blind image super-resolution with degradation-aware adaptation","volume-title":"Proc. ACCV","author":"Wang"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00319"},{"key":"ref32","first-page":"1126","article-title":"Model-agnostic meta-learning for fast adaptation of deep networks","volume-title":"Proc. 34th Int. Conf. Mach. Learn.","volume":"70","author":"Finn"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CAC59555.2023.10451732"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1503.02531"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2024.3368923"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00712"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01131"},{"key":"ref38","first-page":"1945","article-title":"Batch renormalization: Towards reducing minibatch dependence in batch-normalized models","volume-title":"Proc. NeurIPS","volume":"30","author":"Ioffe"},{"key":"ref39","article-title":"Gaussian error linear units (GELUs)","author":"Hendrycks","year":"2016","journal-title":"arXiv:1606.08415"},{"key":"ref40","article-title":"Representation learning with contrastive predictive coding","author":"van den Oord","year":"2018","journal-title":"arXiv:1807.03748"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01167"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.149"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.5244\/C.26.135"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-27413-8_47"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2001.937655"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7299156"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW56347.2022.00068"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19797-0_33"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2003.819861"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00068"},{"key":"ref51","first-page":"4061","article-title":"Decoupled weight decay regularization","volume-title":"Proc. ICLR","author":"Loshchilov"},{"key":"ref52","first-page":"1769","article-title":"SGDR: Stochastic gradient descent with warm restarts","volume-title":"Proc. ICLR","author":"Loshchilov"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2662206"},{"key":"ref54","article-title":"Redundant features can hurt robustness to distributions shift","volume-title":"Proc. ICML","author":"Jimenez"}],"container-title":["IEEE Transactions on Image Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/83\/10795784\/10964088.pdf?arnumber=10964088","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T18:53:13Z","timestamp":1753901593000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10964088\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":54,"URL":"https:\/\/doi.org\/10.1109\/tip.2025.3558442","relation":{},"ISSN":["1057-7149","1941-0042"],"issn-type":[{"value":"1057-7149","type":"print"},{"value":"1941-0042","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}