{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T02:53:40Z","timestamp":1782269620245,"version":"3.54.5"},"reference-count":82,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,10,19]],"date-time":"2025-10-19T00:00:00Z","timestamp":1760832000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,10,19]],"date-time":"2025-10-19T00:00:00Z","timestamp":1760832000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001321","name":"National Research Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001321","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100014188","name":"MSIT","doi-asserted-by":"publisher","award":["RS-2025-00562400"],"award-info":[{"award-number":["RS-2025-00562400"]}],"id":[{"id":"10.13039\/501100014188","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,19]]},"DOI":"10.1109\/iccv51701.2025.02268","type":"proceedings-article","created":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T19:45:49Z","timestamp":1777491949000},"page":"24467-24477","source":"Crossref","is-referenced-by-count":7,"title":["Emulating Self-attention with Convolution for Efficient Image Super-Resolution"],"prefix":"10.1109","author":[{"given":"Dongheon","family":"Lee","sequence":"first","affiliation":[{"name":"University of Seoul,Machine Intelligence Laboratory,Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seokju","family":"Yun","sequence":"additional","affiliation":[{"name":"University of Seoul,Machine Intelligence Laboratory,Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Youngmin","family":"Ro","sequence":"additional","affiliation":[{"name":"University of Seoul,Machine Intelligence Laboratory,Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.150"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.52202\/079017-1761"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.5244\/C.26.135"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00318"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01212"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00531"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.02142"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00852"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.52202\/068431-1847"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.52202\/068431-1189"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3045810"},{"key":"ref12","first-page":"11963","article-title":"Scaling up your kernels to $31 \\times 31$: Revisiting large kernel design in cnns","volume-title":"CVPR","author":"Ding","year":"2022"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2439281"},{"key":"ref14","article-title":"Flex attention: A programming model for generating optimized attention kernels","author":"Dong","year":"2024","journal-title":"arXiv preprint"},{"key":"ref15","article-title":"An image is worth $16 \\times 16$ words: Transformers for image recognition at scale","volume-title":"ICLR","author":"Dosovitskiy","year":"2020"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW53098.2021.00283"},{"key":"ref17","article-title":"Mamba: Linear-time sequence modeling with selective state spaces","author":"Gu","year":"2023","journal-title":"arXiv preprint"},{"key":"ref18","article-title":"Efficiently modeling long sequences with structured state spaces","volume-title":"ICLR","author":"Gu","year":"2022"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00908"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-72649-1_13"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52734.2025.02619"},{"key":"ref22","article-title":"On the connection between local attention and dynamic depth-wise convolution","volume-title":"ICLR","author":"Han","year":"2022"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-72684-2_17"},{"key":"ref24","article-title":"Gans trained by a two time-scale update rule converge to a local nash equilibrium","volume":"30","author":"Heusel","year":"2017","journal-title":"NeurIPS"},{"key":"ref25","article-title":"Mobilenets: Efficient convolutional neural networks for mobile vision applications","author":"Howard","year":"2017","journal-title":"arXiv preprint"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7299156"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00510"},{"key":"ref28","first-page":"1637","article-title":"Deeplyrecursive convolutional network for image super-resolution","volume-title":"CVPR","author":"Kim","year":"2016"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.182"},{"key":"ref30","article-title":"Adam: a method for stochastic optimization","volume-title":"ICLR","author":"Kingma","year":"2014"},{"key":"ref31","first-page":"3519","article-title":"Similarity of neural network representations revisited","volume-title":"ICML","author":"Kornblith","year":"2019"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00197"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2023\/121"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW59228.2023.00178"},{"key":"ref35","first-page":"3867","article-title":"Feedback network for image superresolution","volume-title":"CVPR","author":"Li","year":"2019"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW54120.2021.00210"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.151"},{"key":"ref38","article-title":"More convnets in the 2020s: Scaling up kernels beyond $51 \\times 51$ using sparsity","volume-title":"ICLR","author":"Liu","year":"2023"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/3581783.3612128"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"ref41","article-title":"Decoupled weight decay regularization","volume-title":"ICLR","author":"Loshchilov","year":"2019"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2001.937655"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-016-4020-z"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/lsp.2012.2227726"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-72643-9_2"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/WACV61041.2025.00263"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v39i6.32687"},{"key":"ref48","article-title":"How do vision transformers work?","volume-title":"ICLR","author":"Park","year":"2022"},{"issue":"140","key":"ref49","first-page":"1","article-title":"Exploring the limits of transfer learning with a unified text-to-text transformer","volume":"21","author":"Raffel","year":"2020","journal-title":"Journal of machine learning research"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.207"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2023.127063"},{"key":"ref52","first-page":"17314","article-title":"Shufflemixer: An efficient convet for image super-resolution","volume":"35","author":"Sun","year":"2022","journal-title":"NeurIPS"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr.2017.298"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.149"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.02143"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i2.25353"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00070"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW54120.2021.00217"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58598-3_7"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01318"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2024.3477350"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW59228.2023.00135"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW56347.2022.00126"},{"key":"ref65","article-title":"Cogvideox: Text-to-video diffusion models with an expert transformer","author":"Yang","year":"2024","journal-title":"arXiv preprint"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52734.2025.01464"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/WACV56688.2023.00493"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00550"},{"key":"ref69","first-page":"5728","article-title":"Restormer: efficient attention transformer for high-resolution image restoration","volume-title":"CVPR","author":"Zamir","year":"2022"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-27413-8_47"},{"key":"ref71","article-title":"Accurate image restoration with attention retractable transformer","volume-title":"ICLR","author":"Zhang","year":"2023"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00475"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00276"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00068"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19790-1_39"},{"key":"ref76","article-title":"Hit-sr: Hierarchical transformer for efficient attention image super-resolution","volume-title":"ECCV","author":"Zhang","year":"2024"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1807.02758"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00262"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-67070-2_3"},{"key":"ref80","article-title":"Ups: Unified projection sharing for lightweight single-image super-resolution and beyond","author":"Zhou","year":"2024","journal-title":"NeurIPS"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-25063-7_16"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01174"}],"event":{"name":"2025 IEEE\/CVF International Conference on Computer Vision (ICCV)","location":"Honolulu, HI, USA","start":{"date-parts":[[2025,10,19]]},"end":{"date-parts":[[2025,10,25]]}},"container-title":["2025 IEEE\/CVF International Conference on Computer Vision (ICCV)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11443115\/11443287\/11443322.pdf?arnumber=11443322","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T06:45:12Z","timestamp":1777531512000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11443322\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,19]]},"references-count":82,"URL":"https:\/\/doi.org\/10.1109\/iccv51701.2025.02268","relation":{},"subject":[],"published":{"date-parts":[[2025,10,19]]}}}