{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T05:34:56Z","timestamp":1772516096352,"version":"3.50.1"},"reference-count":66,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2025,3,1]],"date-time":"2025-03-01T00:00:00Z","timestamp":1740787200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,3,1]],"date-time":"2025-03-01T00:00:00Z","timestamp":1740787200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,3,1]],"date-time":"2025-03-01T00:00:00Z","timestamp":1740787200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"National Key RD Program of China","award":["2022YFA1004100"],"award-info":[{"award-number":["2022YFA1004100"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U19A2073"],"award-info":[{"award-number":["U19A2073"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Pattern Anal. Mach. Intell."],"published-print":{"date-parts":[[2025,3]]},"DOI":"10.1109\/tpami.2024.3379736","type":"journal-article","created":{"date-parts":[[2024,3,20]],"date-time":"2024-03-20T18:20:20Z","timestamp":1710958820000},"page":"1348-1361","source":"Crossref","is-referenced-by-count":7,"title":["Self-Supervised Learning for Real-World Super-Resolution From Dual and Multiple Zoomed Observations"],"prefix":"10.1109","volume":"47","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5758-5949","authenticated-orcid":false,"given":"Zhilu","family":"Zhang","sequence":"first","affiliation":[{"name":"Faculty of Computing, Harbin Institute of Technology, Harbin, Heilongjiang, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-6849-0028","authenticated-orcid":false,"given":"Ruohao","family":"Wang","sequence":"additional","affiliation":[{"name":"Faculty of Computing, Harbin Institute of Technology, Harbin, Heilongjiang, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8025-346X","authenticated-orcid":false,"given":"Hongzhi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Faculty of Computing, Harbin Institute of Technology, Harbin, Heilongjiang, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3330-783X","authenticated-orcid":false,"given":"Wangmeng","family":"Zuo","sequence":"additional","affiliation":[{"name":"Faculty of Computing, Harbin Institute of Technology, Harbin, Heilongjiang, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2439281"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.19"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.151"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01234-2_18"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW54120.2021.00210"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00817"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58548-8_14"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00845"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00583"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00630"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00214"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00584"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19797-0_19"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19800-7_38"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00201"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00431"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00388"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58598-3_7"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01730"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19797-0_35"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00344"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3351084"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-66823-5_8"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00488"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01184"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00427"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00170"},{"key":"ref28","article-title":"Unfolding the alternating optimization for blind super resolution","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Luo"},{"key":"ref29","first-page":"284","article-title":"Blind super-resolution kernel estimation using an internal-GAN","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Bell-Kligler"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01046"},{"key":"ref31","article-title":"Density estimation using real NVP","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Dinh"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00406"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01044"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00150"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00475"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW54120.2021.00217"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW50498.2020.00255"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2019.00442"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01318"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00175"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00318"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-67070-2_24"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2019.00274"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00931"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.5244\/C.31.138"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58571-6_13"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01231-1_6"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.316"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.89"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00953"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i2.16181"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01444"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.207"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00367"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00383"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00929"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/iccp51581.2021.9466271"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00576"},{"key":"ref60","article-title":"Very deep convolutional networks for large-scale image recognition","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Simonyan"},{"key":"ref61","article-title":"Adam: A method for stochastic optimization","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Kingma"},{"key":"ref62","first-page":"8024","article-title":"PyTorch: An imperative style, high-performance deep learning library","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Paszke"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2003.819861"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00068"},{"key":"ref65","article-title":"The relativistic discriminator: A key element missing from standard GAN","author":"Jolicoeur-Martineau","year":"2018"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.5555\/2969033.2969125"}],"container-title":["IEEE Transactions on Pattern Analysis and Machine Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/34\/10873290\/10476716.pdf?arnumber=10476716","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,6]],"date-time":"2025-02-06T06:00:19Z","timestamp":1738821619000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10476716\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3]]},"references-count":66,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/tpami.2024.3379736","relation":{},"ISSN":["0162-8828","2160-9292","1939-3539"],"issn-type":[{"value":"0162-8828","type":"print"},{"value":"2160-9292","type":"electronic"},{"value":"1939-3539","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,3]]}}}