{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T10:29:54Z","timestamp":1760956194738,"version":"3.37.3"},"reference-count":71,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"JST"},{"DOI":"10.13039\/501100020964","name":"Fusion Oriented REsearch for disruptive Science and Technology","doi-asserted-by":"publisher","award":["JPMJFR206S"],"award-info":[{"award-number":["JPMJFR206S"]}],"id":[{"id":"10.13039\/501100020964","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Key Research and Development Program of China","award":["2022YFB3903500"],"award-info":[{"award-number":["2022YFB3903500"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42271370"],"award-info":[{"award-number":["42271370"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Comput. Imaging"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/tci.2023.3248943","type":"journal-article","created":{"date-parts":[[2023,2,28]],"date-time":"2023-02-28T18:53:36Z","timestamp":1677610416000},"page":"185-196","source":"Crossref","is-referenced-by-count":4,"title":["Interpretable Deep Attention Prior for Image Restoration and Enhancement"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3410-0643","authenticated-orcid":false,"given":"Wei","family":"He","sequence":"first","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tatsumi","family":"Uezato","sequence":"additional","affiliation":[{"name":"Hitachi, Ltd., Tokyo, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7321-4590","authenticated-orcid":false,"given":"Naoto","family":"Yokoya","sequence":"additional","affiliation":[{"name":"Department of Complexity Science and Engineering, Geoinformatics Unit, RIKEN Center for Advanced Intelligence Project (AIP), The University of Tokyo, Tokyo, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2004.836784"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00325"},{"key":"ref3","first-page":"524","article-title":"Noise2Self: Blind denoising by self-supervision","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Batson","year":"2019"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2005.38"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICCSA54496.2021.00016"},{"key":"ref6","article-title":"The spectral bias of the deep image prior","volume-title":"Proc. Adv. Neural Inf. Process. Syst. Workshops","author":"Chakrabarty","year":"2019"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58523-5_26"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5762"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01249"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00559"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3130800.3130810"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2007.901238"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01193"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01128"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1364\/OE.15.014013"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2888491"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01553"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.213"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.108280"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3027563"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3101916"},{"key":"ref22","article-title":"Deep decoder: Concise image representations from untrained non-convolutional networks","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Heckel","year":"2019"},{"key":"ref23","article-title":"Denoising and regularization via exploiting the structural bias of convolutional generators","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Heckel","year":"2020"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00504"},{"key":"ref25","first-page":"5156","article-title":"Transformers are RNNs: Fast autoregressive transformers with linear attention","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Katharopoulos","year":"2020"},{"key":"ref26","article-title":"Adam: A method for stochastic optimization","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Kingma","year":"2015"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00223"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/882262.882264"},{"key":"ref29","article-title":"Noise2Noise: Learning image restoration without clean data","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Lehtinen","year":"2018"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr42600.2020.01031"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW54120.2021.00210"},{"key":"ref32","article-title":"Non-local recurrent network for image restoration","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"31","author":"Liu","year":"2018"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01252-6_6"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2019.8682856"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2873587"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2009.5459452"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2001.937655"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2009.03.008"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-023-01843-5"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00262"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01706"},{"key":"ref42","first-page":"4055","article-title":"Image transformer","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Parmar","year":"2018"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.3009207"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00196"},{"key":"ref45","article-title":"Stand-alone self-attention in vision models","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Ramachandran","year":"2019"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-88682-2_38"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/tgrs.2021.3108515"},{"key":"ref49","first-page":"3531","article-title":"Efficient attention: Attention with linear complexities","volume-title":"Proc. Winter Conf. Appl. Comput. Vis.","author":"Shen","year":"2021"},{"key":"ref50","article-title":"Deep hyperspectral prior: Denoising, inpainting, super-resolution","volume-title":"Proc. Int. Conf. Image Process.","author":"Sidorov","year":"2019"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2020.2977214"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2020.07.025"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58539-6_6"},{"key":"ref54","first-page":"9446","article-title":"Deep image prior","volume-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit.","author":"Ulyanov","year":"2018"},{"article-title":"Compressed sensing with deep image prior and learned regularization","year":"2018","author":"Veen","key":"ref55"},{"key":"ref56","article-title":"Attention is all you need","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Vaswani","year":"2017"},{"key":"ref57","first-page":"99","article-title":"Quality of high resolution synthesised images: Is there a simple criterion?","volume-title":"Proc. 3rd Conf. Fusion Earth Data: Merging Point Meas., Raster Maps Remotely Sensed Images","author":"Wald","year":"2000"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00813"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.2982166"},{"key":"ref60","first-page":"681","article-title":"Bayesian learning via stochastic gradient Langevin dynamics","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Welling","year":"2011"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.3390\/sym13112114"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3037923"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00322"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00564"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.7717\/peerj-cs.970"},{"key":"ref66","article-title":"Residual non-local attention networks for image restoration","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Zhang","year":"2019"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2019.2900419"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01009"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.2986313"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1080\/014311698215973"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1109\/WACVW54805.2022.00081"}],"container-title":["IEEE Transactions on Computational Imaging"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6745852\/10038323\/10054493.pdf?arnumber=10054493","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,13]],"date-time":"2024-02-13T15:26:19Z","timestamp":1707837979000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10054493\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":71,"URL":"https:\/\/doi.org\/10.1109\/tci.2023.3248943","relation":{},"ISSN":["2333-9403","2334-0118","2573-0436"],"issn-type":[{"type":"electronic","value":"2333-9403"},{"type":"electronic","value":"2334-0118"},{"type":"print","value":"2573-0436"}],"subject":[],"published":{"date-parts":[[2023]]}}}