{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T14:25:58Z","timestamp":1740147958444,"version":"3.37.3"},"reference-count":80,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2021,2,1]],"date-time":"2021-02-01T00:00:00Z","timestamp":1612137600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,2,1]],"date-time":"2021-02-01T00:00:00Z","timestamp":1612137600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,2,1]],"date-time":"2021-02-01T00:00:00Z","timestamp":1612137600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE J. Sel. Top. Signal Process."],"published-print":{"date-parts":[[2021,2]]},"DOI":"10.1109\/jstsp.2021.3049641","type":"journal-article","created":{"date-parts":[[2021,1,7]],"date-time":"2021-01-07T14:31:57Z","timestamp":1610029917000},"page":"279-294","source":"Crossref","is-referenced-by-count":2,"title":["Multi\u2013Grid Back\u2013Projection Networks"],"prefix":"10.1109","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6293-9668","authenticated-orcid":false,"given":"Pablo Navarrete","family":"Michelini","sequence":"first","affiliation":[]},{"given":"Wenbin","family":"Chen","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5896-4329","authenticated-orcid":false,"given":"Hanwen","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Dan","family":"Zhu","sequence":"additional","affiliation":[]},{"given":"Xingqun","family":"Jiang","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"article-title":"Deep back-projection networks for single image super-resolution","year":"2019","author":"haris","key":"ref73"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-11021-5_8"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.481"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2019.00446"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2019.06.103"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-11021-5_7"},{"key":"ref74","first-page":"63","article-title":"Esrgan: Enhanced super-resolution generative adversarial networks","author":"wang","year":"0","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00179"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-11021-5_4"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2018.00130"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-11021-5_2"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-11021-5_9"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33014642"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-11021-5_21"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00652"},{"key":"ref30","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-030-66823-5_4","article-title":"AIM 2020 challenge on video extreme super-resolution: Methods and results","author":"fuoli","year":"2020"},{"key":"ref37","article-title":"Progressive growing of GANs for improved quality, stability, and variation","author":"karras","year":"0","journal-title":"Proc Int Conf Learn Representations"},{"journal-title":"Multigrid","year":"2001","author":"trottenberg","key":"ref36"},{"key":"ref35","first-page":"3399","article-title":"MGBPv2: Scaling up multi-grid back-projection networks","author":"michelini","year":"0","journal-title":"Proc IEEE\/CVF Int Conf Compute Vis Workshop (ICCVW)"},{"key":"ref34","first-page":"3","article-title":"Multi-scale recursive and perception-distortion controllable image super-resolution","author":"michelini","year":"0","journal-title":"Proc Comput Vision ECCV 2018 Worksh"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.181"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.150"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.2968521"},{"key":"ref63","first-page":"711","article-title":"On Single Image Scale-Up Using Sparse-Representations","author":"zeyde","year":"2010","journal-title":"Proc Int Conf Curves Surfaces"},{"article-title":"VESR-Net: The winning solution to Youku video enhancement and super-resolution challenge","year":"2020","author":"chen","key":"ref28"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2001.937655"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2019.00247"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7299156"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-016-4020-z"},{"key":"ref29","first-page":"294","article-title":"Image super-resolution using very deep residual channel attention networks","author":"zhang","year":"0","journal-title":"Proc Eur Conf Comput Vis"},{"article-title":"Evaluation code for residual dense networks","year":"2018","author":"zhang","key":"ref67"},{"key":"ref68","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"0","journal-title":"International Conference on Learning Representations (ICLR)"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2019.00251"},{"article-title":"Digital Signal Processing, Ser. Prentice Hall International Editions","year":"2007","author":"proakis","key":"ref2"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2014.2302331"},{"key":"ref20","first-page":"5224","article-title":"Handling motion blur in multi-frame super-resolution","author":"ma","year":"0","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.68"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TCI.2016.2532323"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.479"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.274"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00340"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-018-01144-2"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1007\/BFb0004544"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1016\/1049-9652(91)90045-L"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.618"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.182"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46475-6_25"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-16817-3_8"},{"article-title":"Learning to maintain natural image statistics","year":"2018","author":"mechrez","key":"ref55"},{"key":"ref54","article-title":"The relativistic discriminator: A key element missing from standard GAN","author":"jolicoeur-martineau","year":"2018","journal-title":"Int Conf Learn Representations"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2865304"},{"article-title":"Introduction to Algorithms","year":"2009","author":"cormen","key":"ref52"},{"key":"ref10","first-page":"770","article-title":"Deep residual learning for image recognition,&#x201D; Comput. Vis. Pattern Recognit.","author":"he","year":"2016"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.151"},{"key":"ref40","first-page":"3467","article-title":"AIM 2019 challenge on image extreme super-resolution: Methods and results","author":"shuhang","year":"2019","journal-title":"IEEE\/CVF Int Conf Compute vis Workshop (ICCVW)"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00262"},{"key":"ref14","first-page":"7132","article-title":"Squeeze-and-excitation networks,&#x201D; Comput. Vis. Pattern Recognit.","author":"hu","year":"2018"},{"key":"ref15","first-page":"286","article-title":"Image super-resolution using very deep residual channel attention networks","author":"zhang","year":"0","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref16","first-page":"7794","article-title":"Non-local neural networks,&#x201D; Comput. Vis. Pattern Recognit.","author":"wang","year":"2018"},{"key":"ref17","article-title":"Residual non-local attention networks for image restoration","author":"zhang","year":"0","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2004.834669"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.127"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00485"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.1991.151035"},{"article-title":"A Wavelet Tour of Signal Processing","year":"1998","author":"mallat","key":"ref3"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/s11075-007-9092-4"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/83.951537"},{"key":"ref8","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"lecun","year":"2015","journal-title":"Nature"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2003.1203207"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.149"},{"key":"ref9","first-page":"184","article-title":"Learning a deep convolutional network for image super-resolution","author":"dong","year":"0","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1088\/0954-898X_5_4_006"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01264-9_47"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2012.2214050"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2012.2227726"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2003.819861"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2010.2042111"},{"key":"ref44","doi-asserted-by":"crossref","first-page":"694","DOI":"10.1007\/978-3-319-46475-6_43","article-title":"Perceptual losses for real-time style transfer and super-resolution","author":"johnson","year":"2016","journal-title":"Computer Vision-ECCV 2016"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2005.859378"}],"container-title":["IEEE Journal of Selected Topics in Signal Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/4200690\/9359898\/09314918.pdf?arnumber=9314918","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,10]],"date-time":"2022-12-10T22:20:24Z","timestamp":1670710824000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9314918\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,2]]},"references-count":80,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/jstsp.2021.3049641","relation":{},"ISSN":["1932-4553","1941-0484"],"issn-type":[{"type":"print","value":"1932-4553"},{"type":"electronic","value":"1941-0484"}],"subject":[],"published":{"date-parts":[[2021,2]]}}}