{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T10:01:34Z","timestamp":1740132094318,"version":"3.37.3"},"reference-count":67,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"12","license":[{"start":{"date-parts":[[2022,12,1]],"date-time":"2022-12-01T00:00:00Z","timestamp":1669852800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"name":"R&#x0026;D program for Advanced Integrated-intelligence for Identification"},{"DOI":"10.13039\/501100001321","name":"National Research Foundation","doi-asserted-by":"publisher","award":["NRF-2018M3E3A1057289"],"award-info":[{"award-number":["NRF-2018M3E3A1057289"]}],"id":[{"id":"10.13039\/501100001321","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Yonsei University Research Fund","award":["2021-22-0001"],"award-info":[{"award-number":["2021-22-0001"]}]},{"name":"Ministry of Science and ICT"},{"name":"ICT Creative Consilience program","award":["IITP-2021-2020-0-01819"],"award-info":[{"award-number":["IITP-2021-2020-0-01819"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Pattern Anal. Mach. Intell."],"published-print":{"date-parts":[[2022,12,1]]},"DOI":"10.1109\/tpami.2021.3123679","type":"journal-article","created":{"date-parts":[[2021,10,29]],"date-time":"2021-10-29T19:25:21Z","timestamp":1635535521000},"page":"9102-9118","source":"Crossref","is-referenced-by-count":2,"title":["Pyramidal Semantic Correspondence Networks"],"prefix":"10.1109","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0991-6165","authenticated-orcid":false,"given":"Sangryul","family":"Jeon","sequence":"first","affiliation":[{"name":"School of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2927-6273","authenticated-orcid":false,"given":"Seungryong","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Korea University, Seoul, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4825-5240","authenticated-orcid":false,"given":"Dongbo","family":"Min","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Ewha Womans University, Seoul, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3715-0331","authenticated-orcid":false,"given":"Kwanghoon","family":"Sohn","sequence":"additional","affiliation":[{"name":"School of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00210"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.242"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.442"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2009.77"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1023\/B:VISI.0000029664.99615.94"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00349"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00383"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.306"},{"key":"ref35","first-page":"2414","article-title":"Universal correspondence network","author":"choy","year":"2016","journal-title":"Proc 30th Int Conf Neural Inf Process Syst"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-013-0620-5"},{"article-title":"Adam: A method for stochastic optimization","year":"2014","author":"kingma","key":"ref60"},{"article-title":"Very deep convolutional networks for large-scale image recognition","year":"2014","author":"simonyan","key":"ref62"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1006\/cviu.1999.0832"},{"key":"ref63","first-page":"1601","article-title":"Do convnets learn correspondence?","author":"long","year":"2014","journal-title":"Proc 27th Int Conf Neural Inf Process Syst"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2724510"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3013620"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.460"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58604-1_38"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01264-9_21"},{"key":"ref29","doi-asserted-by":"crossref","first-page":"594","DOI":"10.1109\/TPAMI.2006.79","article-title":"One-shot learning of object categories","volume":"28","author":"li","year":"2006","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2014.6836101"},{"key":"ref2","first-page":"815","article-title":"SIFT Flow: Dense correspondence across scenes and its applications","volume":"33","author":"liu","year":"2011","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/1964921.1964965"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00723"},{"key":"ref22","first-page":"1651","article-title":"Neighbourhood consensus networks","author":"rocco","year":"2018","journal-title":"Proc 32nd Int Conf Neural Inf Process Syst"},{"key":"ref21","first-page":"6126","article-title":"Recurrent transformer networks for semantic correspondence","author":"kim","year":"2018","journal-title":"Proc 32nd Int Conf Neural Inf Process Syst"},{"key":"ref24","first-page":"2017","article-title":"Spatial transformer networks","author":"jaderberg","year":"2015","journal-title":"Proc 28th Int Conf Neural Inf Process Syst"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00238"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01231-1_22"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2007.383172"},{"key":"ref50","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc 25th Int Conf Neural Inf Process Syst"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-009-0275-4"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.254"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-009-0275-4"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1145\/1141911.1141920"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.178"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.17"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00285"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.299"},{"key":"ref10","first-page":"2758","article-title":"FlowNet: Learning optical flow with convolutional networks","author":"fischer","year":"2015","journal-title":"Proc IEEE Int Conf Comput Vis"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01021"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.179"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.378"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.203"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.73"},{"key":"ref15","first-page":"1601","article-title":"Do convnets learn correspondence?","author":"long","year":"2014","journal-title":"Proc 27th Int Conf Neural Inf Process Syst"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.628"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.485"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.12"},{"key":"ref19","first-page":"349","article-title":"Attentive semantic alignment with offset-aware correlation kernels","author":"hongsuck seo","year":"2018","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.435"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.299"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1023\/A:1014573219977"},{"key":"ref5","first-page":"1191","article-title":"FlowWeb: Joint image set alignment by weaving consistent, pixel-wise correspondences","author":"zhou","year":"2015","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.699"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-016-0908-3"},{"key":"ref7","first-page":"2287","article-title":"Stereo matching by training a convolutional neural network to compare image patches","volume":"17","author":"zbontar","year":"2016","journal-title":"J Mach Learn Res"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33783-3_44"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00825"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00096"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298745"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206697"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58555-6_21"},{"article-title":"SPair-71k: A large-scale benchmark for semantic correspondence","year":"2019","author":"min","key":"ref41"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.348"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00452"}],"container-title":["IEEE Transactions on Pattern Analysis and Machine Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/34\/9940447\/09594706.pdf?arnumber=9594706","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,5]],"date-time":"2022-12-05T23:11:49Z","timestamp":1670281909000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9594706\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,1]]},"references-count":67,"journal-issue":{"issue":"12"},"URL":"https:\/\/doi.org\/10.1109\/tpami.2021.3123679","relation":{},"ISSN":["0162-8828","2160-9292","1939-3539"],"issn-type":[{"type":"print","value":"0162-8828"},{"type":"electronic","value":"2160-9292"},{"type":"electronic","value":"1939-3539"}],"subject":[],"published":{"date-parts":[[2022,12,1]]}}}