{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T06:06:37Z","timestamp":1759989997779,"version":"3.41.2"},"reference-count":39,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100019091","name":"Key Research and Development Program of Hubei Province of China","doi-asserted-by":"publisher","award":["2024BBB055"],"award-info":[{"award-number":["2024BBB055"]}],"id":[{"id":"10.13039\/501100019091","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100017941","name":"Philosophy and Social Science Foundation of Hubei Province","doi-asserted-by":"publisher","award":["19Q062"],"award-info":[{"award-number":["19Q062"]}],"id":[{"id":"10.13039\/100017941","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/access.2025.3590252","type":"journal-article","created":{"date-parts":[[2025,7,17]],"date-time":"2025-07-17T18:00:13Z","timestamp":1752775213000},"page":"127351-127367","source":"Crossref","is-referenced-by-count":1,"title":["GeoAT: Geometry-Aware Attention Feature Matching Network"],"prefix":"10.1109","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-6283-0338","authenticated-orcid":false,"given":"Yan","family":"Li","sequence":"first","affiliation":[{"name":"School of Science, Hubei University of Technology, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2815-6694","authenticated-orcid":false,"given":"Yingdan","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Science, Hubei University of Technology, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Ming","sequence":"additional","affiliation":[{"name":"CCCC Second Highway Survey and Design Institute Company Ltd., Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yong","family":"Zhang","sequence":"additional","affiliation":[{"name":"Computer School, Central China Normal University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhesheng","family":"Cheng","sequence":"additional","affiliation":[{"name":"School of Science, Hubei University of Technology, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.445"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.5244\/C.26.76"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00897"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00752"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2015.2463671"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2017.2705103"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00319"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01225-0_20"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00593"},{"key":"ref10","article-title":"Deep image homography estimation","author":"DeTone","year":"2016","journal-title":"arXiv:1606.03798"},{"key":"ref11","article-title":"D2-net: A trainable CNN for joint detection and description of local features","author":"Dusmanu","year":"2019","journal-title":"arXiv:1905.03561"},{"key":"ref12","first-page":"6237","article-title":"LF-net: Learning local features from images","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Ono"},{"key":"ref13","first-page":"12405","article-title":"R2D2: Reliable and repeatable detector and descriptor","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"32","author":"Revaud"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00499"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1023\/b:visi.0000029664.99615.94"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2011.6126544"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00881"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00615"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00566"},{"key":"ref20","first-page":"1658","article-title":"Neighbourhood consensus networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Rocco"},{"key":"ref21","first-page":"17346","article-title":"Dual-resolution correspondence networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Li"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00629"},{"key":"ref23","article-title":"QuadTree attention for vision transformers","author":"Tang","year":"2022","journal-title":"arXiv:2201.02767"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19824-3_2"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.02097"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref27","article-title":"An image is worth 16\u00d716 words: Transformers for image recognition at scale","author":"Dosovitskiy","year":"2020","journal-title":"arXiv:2010.11929"},{"key":"ref28","first-page":"5156","article-title":"Transformers are RNNs: Fast autoregressive transformers with linear attention","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Katharopoulos"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.179"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58536-5_24"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2019.00115"},{"key":"ref32","first-page":"14254","article-title":"DISK: Learning local features with policy gradient","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Tyszkiewicz"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00218"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.410"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2018.00060"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58545-7_35"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.272"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33709-3_54"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/10820123\/11083592.pdf?arnumber=11083592","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,26]],"date-time":"2025-07-26T07:38:49Z","timestamp":1753515529000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11083592\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":39,"URL":"https:\/\/doi.org\/10.1109\/access.2025.3590252","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2025]]}}}