{"id":"https://openalex.org/W4392543656","doi":"https://doi.org/10.1109/tcsvt.2024.3374772","title":"MC-Net: Integrating Multi-Level Geometric Context for Two-View Correspondence Learning","display_name":"MC-Net: Integrating Multi-Level Geometric Context for Two-View Correspondence Learning","publication_year":2024,"publication_date":"2024-03-07","ids":{"openalex":"https://openalex.org/W4392543656","doi":"https://doi.org/10.1109/tcsvt.2024.3374772"},"language":"en","primary_location":{"id":"doi:10.1109/tcsvt.2024.3374772","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2024.3374772","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Circuits and Systems for Video Technology","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103012164","display_name":"Zizhuo Li","orcid":"https://orcid.org/0000-0003-0986-4924"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zizhuo Li","raw_affiliation_strings":["Electronic Information School, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Electronic Information School, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102626192","display_name":"Chunbao Su","orcid":"https://orcid.org/0009-0005-7513-346X"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunbao Su","raw_affiliation_strings":["Electronic Information School, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Electronic Information School, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100366841","display_name":"Fan Fan","orcid":"https://orcid.org/0000-0002-7507-1810"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Fan","raw_affiliation_strings":["Electronic Information School, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Electronic Information School, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002872664","display_name":"Jun Huang","orcid":"https://orcid.org/0000-0001-5893-4090"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Huang","raw_affiliation_strings":["Electronic Information School, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Electronic Information School, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040010053","display_name":"Jiayi Ma","orcid":"https://orcid.org/0000-0003-3264-3265"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiayi Ma","raw_affiliation_strings":["Electronic Information School, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Electronic Information School, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5103012164"],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":1.4957,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.82447771,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"34","issue":"8","first_page":"7550","last_page":"7565"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9621999859809875,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9621999859809875,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9592000246047974,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9397000074386597,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6366803050041199},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5979779362678528},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5096609592437744},{"id":"https://openalex.org/keywords/net","display_name":"Net (polyhedron)","score":0.507599949836731},{"id":"https://openalex.org/keywords/context-model","display_name":"Context model","score":0.4742259681224823},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3616744875907898},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3569718599319458},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3511589467525482},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.09963783621788025}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6366803050041199},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5979779362678528},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5096609592437744},{"id":"https://openalex.org/C14166107","wikidata":"https://www.wikidata.org/wiki/Q253829","display_name":"Net (polyhedron)","level":2,"score":0.507599949836731},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.4742259681224823},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3616744875907898},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3569718599319458},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3511589467525482},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.09963783621788025},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsvt.2024.3374772","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2024.3374772","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Circuits and Systems for Video Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3299598301","display_name":null,"funder_award_id":"U23B2050","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3375496651","display_name":null,"funder_award_id":"2023A1515012834","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G415731887","display_name":null,"funder_award_id":"62276192","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":68,"referenced_works":["https://openalex.org/W1561797649","https://openalex.org/W1821109219","https://openalex.org/W1976794880","https://openalex.org/W1980544393","https://openalex.org/W1985238052","https://openalex.org/W1986280275","https://openalex.org/W2004895663","https://openalex.org/W2033819227","https://openalex.org/W2071730188","https://openalex.org/W2085261163","https://openalex.org/W2106199912","https://openalex.org/W2111073598","https://openalex.org/W2114712988","https://openalex.org/W2130017587","https://openalex.org/W2151103935","https://openalex.org/W2171490473","https://openalex.org/W2194775991","https://openalex.org/W2250384498","https://openalex.org/W2471962767","https://openalex.org/W2579352318","https://openalex.org/W2740418457","https://openalex.org/W2740578684","https://openalex.org/W2754925132","https://openalex.org/W2907492528","https://openalex.org/W2951019013","https://openalex.org/W2962705366","https://openalex.org/W2962828767","https://openalex.org/W2963674285","https://openalex.org/W2963748588","https://openalex.org/W2964157791","https://openalex.org/W2967756832","https://openalex.org/W2990655570","https://openalex.org/W3034275286","https://openalex.org/W3034373437","https://openalex.org/W3035563186","https://openalex.org/W3039458201","https://openalex.org/W3043075211","https://openalex.org/W3047057232","https://openalex.org/W3166285241","https://openalex.org/W3167674261","https://openalex.org/W3176247000","https://openalex.org/W3192804777","https://openalex.org/W3203518786","https://openalex.org/W3203615845","https://openalex.org/W3204035704","https://openalex.org/W3206918971","https://openalex.org/W3216892772","https://openalex.org/W4200410897","https://openalex.org/W4226217930","https://openalex.org/W4283379347","https://openalex.org/W4285803058","https://openalex.org/W4297733535","https://openalex.org/W4312322996","https://openalex.org/W4312344182","https://openalex.org/W4312581984","https://openalex.org/W4365807712","https://openalex.org/W4376481231","https://openalex.org/W4379116581","https://openalex.org/W4379528781","https://openalex.org/W4380136644","https://openalex.org/W4380765800","https://openalex.org/W4382239971","https://openalex.org/W4385245566","https://openalex.org/W4385764485","https://openalex.org/W4387197150","https://openalex.org/W4387917939","https://openalex.org/W6763422710","https://openalex.org/W6853486084"],"related_works":["https://openalex.org/W2349222429","https://openalex.org/W1993394192","https://openalex.org/W3117430770","https://openalex.org/W2116230991","https://openalex.org/W2590751808","https://openalex.org/W1972377868","https://openalex.org/W2132709506","https://openalex.org/W2186895195","https://openalex.org/W2151995366","https://openalex.org/W2388933862"],"abstract_inverted_index":{"In":[0],"two-view":[1],"correspondence":[2],"learning,":[3],"prevalent":[4],"multi-layer":[5],"perceptron":[6],"(MLP)-based":[7],"methods":[8],"struggle":[9],"with":[10,136],"context":[11,33,80,146,152],"capturing.":[12],"To":[13,53],"remedy":[14],"this":[15,55,57,218],"issue,":[16],"recent":[17],"advances":[18],"innovatively":[19],"stack":[20],"convolutional":[21],"neural":[22],"network":[23,73],"(CNN)-based":[24],"Resblocks":[25],"sequentially,":[26],"showing":[27],"an":[28],"inherent":[29],"proficiency":[30],"in":[31,45,167,206],"local":[32,77,151],"extraction.":[34],"Yet,":[35],"such":[36],"non-issue-specific":[37],"designs":[38],"inherit":[39],"the":[40,62,65,115,129,161,164,190,199,212,225,238,248],"drawback":[41],"of":[42,64,131,163,169,188],"CNN\u2019s":[43],"difficulty":[44],"aggregating":[46],"global":[47,79,145],"context,":[48],"leading":[49],"to":[50,127,143,159,202,224],"performance":[51,250],"bottlenecks.":[52],"address":[54],"problem,":[56],"prospective":[58],"study":[59],"further":[60],"explores":[61],"potential":[63],"CNN-based":[66],"framework":[67],"and":[68,78,82,90,103,150,194,221,235,246,265],"proposes":[69],"MC-Net,":[70],"a":[71,91,123],"top-performing":[72],"that":[74,86,258],"integrates":[75],"both":[76],"elegantly":[81],"seamlessly.":[83],"Specifically,":[84],"considering":[85],"sparse":[87],"motion":[88,93,117,134,165,181,196,228],"vectors":[89,197,229],"dense":[92,116],"field":[94,118,166],"can":[95],"be":[96],"converted":[97],"into":[98,110],"each":[99,132,232],"other":[100],"through":[101],"interpolation":[102],"sampling,":[104],"we":[105,121,174,216],"first":[106,239],"transform":[107],"unordered":[108],"matches":[109],"image-structured":[111],"data":[112],"by":[113],"estimating":[114],"implicitly.":[119],"Then,":[120],"design":[122],"hierarchical":[124],"rectifying":[125],"module":[126],"rectify":[128],"error":[130],"ordered":[133],"vector":[135],"CNN":[137],"at":[138,183,198],"multiple":[139,263],"levels,":[140],"enabling":[141],"MC-Net":[142,259],"perceive":[144],"from":[147,153,179,231,237],"coarse-level":[148],"features":[149,155,178],"fine-level":[154],"simultaneously,":[156],"which":[157,209],"facilitates":[158],"tackle":[160],"discontinuities":[162],"case":[168],"large":[170],"scene":[171],"disparity.":[172],"Finally,":[173],"reconstruct":[175],"comprehensive":[176],"context-embedded":[177],"rectified":[180,193],"fields":[182],"all":[184],"levels.":[185],"Also,":[186],"instead":[187],"using":[189],"residuals":[191,245],"between":[192,227],"pre-rectified":[195],"same":[200],"layer":[201,240],"reject":[203],"outliers":[204],"as":[205],"previous":[207],"studies,":[208],"seriously":[210],"affects":[211],"inlier":[213],"prediction":[214],"accuracy,":[215],"rethink":[217],"operation":[219],"meticulously":[220],"modify":[222],"it":[223],"difference":[226],"obtained":[230],"layer\u2019s":[233],"reconstruction":[234],"ones":[236],"before":[241],"transformation,":[242],"ensuring":[243],"purer":[244],"enhancing":[247],"matching":[249],"without":[251],"extra":[252],"computational":[253],"burden.":[254],"Extensive":[255],"experiments":[256],"show":[257],"outperforms":[260],"state-of-the-arts":[261],"on":[262],"domains":[264],"datasets.":[266]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
