{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,8]],"date-time":"2026-08-08T18:30:19Z","timestamp":1786213819310,"version":"3.56.0"},"reference-count":121,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"11","license":[{"start":{"date-parts":[[2023,11,1]],"date-time":"2023-11-01T00:00:00Z","timestamp":1698796800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,11,1]],"date-time":"2023-11-01T00:00:00Z","timestamp":1698796800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,11,1]],"date-time":"2023-11-01T00:00:00Z","timestamp":1698796800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"National Key R&amp;D Program of China","award":["2020AAA0105702"],"award-info":[{"award-number":["2020AAA0105702"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U19B2038"],"award-info":[{"award-number":["U19B2038"]}],"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":["61901433"],"award-info":[{"award-number":["61901433"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"University Synergy Innovation Program of Anhui Province","award":["GXXT-2019-025"],"award-info":[{"award-number":["GXXT-2019-025"]}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["WK2100000024"],"award-info":[{"award-number":["WK2100000024"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"name":"USTC Research Funds of the Double First-Class Initiative","award":["YD2100002003"],"award-info":[{"award-number":["YD2100002003"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Pattern Anal. Mach. Intell."],"published-print":{"date-parts":[[2023,11,1]]},"DOI":"10.1109\/tpami.2022.3183612","type":"journal-article","created":{"date-parts":[[2022,6,16]],"date-time":"2022-06-16T19:35:12Z","timestamp":1655408112000},"page":"12978-12995","source":"Crossref","is-referenced-by-count":347,"title":["Image De-Raining Transformer"],"prefix":"10.1109","volume":"45","author":[{"given":"Jie","family":"Xiao","sequence":"first","affiliation":[{"name":"School of Information Science and Technology, University of Science and Technology of China, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8036-4071","authenticated-orcid":false,"given":"Xueyang","family":"Fu","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, University of Science and Technology of China, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8849-5228","authenticated-orcid":false,"given":"Aiping","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, University of Science and Technology of China, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feng","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, University of Science and Technology of China, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2510-8993","authenticated-orcid":false,"given":"Zheng-Jun","family":"Zha","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, University of Science and Technology of China, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref57","first-page":"385","article-title":"Universal style transfer via feature transforms","author":"li","year":"2017","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00604"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00837"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-020-01416-w"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3126387"},{"key":"ref52","first-page":"10556","article-title":"Retinex-inspired unrolling with cooperative prior architecture search for low-light image enhancement","author":"liu","year":"2021","journal-title":"Proc IEEE Conf Comput Vis and Pattern Recog"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2910412"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3063604"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3052903"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00343"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00258"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3061604"},{"key":"ref48","first-page":"1975","article-title":"Joint transmission map estimation and dehazing using deep networks","volume":"30","author":"zhang","year":"2020","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00337"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-018-01146-0"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00344"},{"key":"ref44","first-page":"295","article-title":"Deep non-blind deconvolution via generalized low-rank approximation","author":"ren","year":"2018","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00311"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46475-6_10"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2011.2179057"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00695"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.247"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.275"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2004.1315077"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00179"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3083076"},{"key":"ref100","first-page":"472","article-title":"UCID: An uncompressed color image database","author":"schaefer","year":"2003","journal-title":"Proc SPIE Storage Retrieval Methods Appl Multimedia"},{"key":"ref101","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2010.161"},{"key":"ref40","first-page":"286","article-title":"Image super-resolution using very deep residual channel attention networks","author":"zhang","year":"2018","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.300"},{"key":"ref34","first-page":"1","article-title":"Residual non-local attention networks for image restoration","author":"zhang","year":"2019","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2839891"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3093396"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2873610"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.276"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.2969348"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2019.2920591"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00262"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2662206"},{"key":"ref24","article-title":"Uformer: A general U-shaped transformer for image restoration","author":"wang","year":"2021"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01212"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00564"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW54120.2021.00210"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2832125"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00813"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/3240508.3240636"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"ref27","first-page":"1","article-title":"An image is worth 16x16 words: Transformers for image recognition at scale","author":"dosovitskiy","year":"2021","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.388"},{"key":"ref13","first-page":"1106","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1989.1.4.541"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref97","article-title":"Bridging nonlinearities and stochastic regularizers with Gaussian error linear units","author":"hendrycks","year":"2016"},{"key":"ref96","article-title":"Layer normalization","author":"ba","year":"2016"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.189"},{"key":"ref99","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.299"},{"key":"ref98","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2003.819861"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3088914"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-021-01466-8"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-019-01235-8"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.2968521"},{"key":"ref93","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.106"},{"key":"ref92","doi-asserted-by":"publisher","DOI":"10.1113\/jphysiol.1960.sp006596"},{"key":"ref95","first-page":"7281","article-title":"HRFormer: High-resolution vision transformer for dense predict","author":"yuan","year":"2021","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref94","first-page":"1","article-title":"On the relationship between self-attention and convolutional layers","author":"cordonnier","year":"2020","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref91","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.97"},{"key":"ref90","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00062"},{"key":"ref89","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00009"},{"key":"ref86","first-page":"10347","article-title":"Training data-efficient image transformers & distillation through attention","author":"touvron","year":"2021","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref85","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","author":"devlin","year":"2018"},{"key":"ref88","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00060"},{"key":"ref87","first-page":"1","article-title":"Deformable DETR: Deformable transformers for end-to-end object detection","author":"zhu","year":"2021","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.1007\/s13042-020-01061-2"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.2995190"},{"key":"ref84","first-page":"5998","article-title":"Attention is all you need","author":"vaswani","year":"2017","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref83","article-title":"Data-driven single image deraining: A comprehensive review and new perspectives","author":"zhang","year":"2021","journal-title":"TechRxiv"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00903"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01458"},{"key":"ref108","first-page":"1","article-title":"How do vision transformers work?","author":"park","year":"2022","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00764"},{"key":"ref109","first-page":"1","article-title":"Anti-oversmoothing in deep vision transformers via the fourier domain analysis: From theory to practice","author":"wang","year":"2022","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref106","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00255"},{"key":"ref107","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N18-2074"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00317"},{"key":"ref104","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.84"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00173"},{"key":"ref105","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.632"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00400"},{"key":"ref102","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00263"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00280"},{"key":"ref103","doi-asserted-by":"publisher","DOI":"10.1049\/el:20080522"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICME.2006.262572"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2005.253"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00745"},{"key":"ref111","first-page":"3","article-title":"Group normalization","author":"wu","year":"2018","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01234-2_16"},{"key":"ref112","article-title":"Instance normalization: The missing ingredient for fast stylization","author":"ulyanov","year":"2016"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01255"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00406"},{"key":"ref110","first-page":"448","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"ioffe","year":"2015","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2019.2895793"},{"key":"ref119","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58595-2_30"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.183"},{"key":"ref117","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58607-2_3"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00079"},{"key":"ref118","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00277"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2019.05.003"},{"key":"ref115","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2007.901238"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2019.2920407"},{"key":"ref116","article-title":"Variational denoising network: Toward blind noise modeling and removal","author":"yue","year":"2019","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.186"},{"key":"ref113","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2691802"},{"key":"ref114","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00182"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2020.2990606"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2020.2993406"},{"key":"ref120","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00849"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2020.2973802"},{"key":"ref121","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00429"}],"container-title":["IEEE Transactions on Pattern Analysis and Machine Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/34\/10269680\/09798773.pdf?arnumber=9798773","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,13]],"date-time":"2023-11-13T19:17:01Z","timestamp":1699903021000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9798773\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,1]]},"references-count":121,"journal-issue":{"issue":"11"},"URL":"https:\/\/doi.org\/10.1109\/tpami.2022.3183612","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":[[2023,11,1]]}}}