{"id":"https://openalex.org/W4313639095","doi":"https://doi.org/10.1109/tpami.2022.3233884","title":"Convolutional Hough Matching Networks for Robust and Efficient Visual Correspondence","display_name":"Convolutional Hough Matching Networks for Robust and Efficient Visual Correspondence","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4313639095","doi":"https://doi.org/10.1109/tpami.2022.3233884","pmid":"https://pubmed.ncbi.nlm.nih.gov/37018584"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2022.3233884","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3233884","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5020055570","display_name":"Juhong Min","orcid":null},"institutions":[{"id":"https://openalex.org/I123900574","display_name":"Pohang University of Science and Technology","ror":"https://ror.org/04xysgw12","country_code":"KR","type":"education","lineage":["https://openalex.org/I123900574"]},{"id":"https://openalex.org/I2799891827","display_name":"Korea Post","ror":"https://ror.org/00p45d091","country_code":"KR","type":"government","lineage":["https://openalex.org/I2799891827","https://openalex.org/I2801339556","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Juhong Min","raw_affiliation_strings":["CSE, POSTECH, Korea"],"affiliations":[{"raw_affiliation_string":"CSE, POSTECH, Korea","institution_ids":["https://openalex.org/I2799891827","https://openalex.org/I123900574"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021971565","display_name":"Seungwook Kim","orcid":"https://orcid.org/0000-0003-1892-7886"},"institutions":[{"id":"https://openalex.org/I123900574","display_name":"Pohang University of Science and Technology","ror":"https://ror.org/04xysgw12","country_code":"KR","type":"education","lineage":["https://openalex.org/I123900574"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seungwook Kim","raw_affiliation_strings":["Graduate School of Artificial Intelligence, Pohang University of Science and Technology, Korea"],"affiliations":[{"raw_affiliation_string":"Graduate School of Artificial Intelligence, Pohang University of Science and Technology, Korea","institution_ids":["https://openalex.org/I123900574"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009444926","display_name":"Minsu Cho","orcid":"https://orcid.org/0000-0001-7030-1958"},"institutions":[{"id":"https://openalex.org/I2799891827","display_name":"Korea Post","ror":"https://ror.org/00p45d091","country_code":"KR","type":"government","lineage":["https://openalex.org/I2799891827","https://openalex.org/I2801339556","https://openalex.org/I4387152098"]},{"id":"https://openalex.org/I123900574","display_name":"Pohang University of Science and Technology","ror":"https://ror.org/04xysgw12","country_code":"KR","type":"education","lineage":["https://openalex.org/I123900574"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Minsu Cho","raw_affiliation_strings":["Computer Science, POSTECH, Korea"],"affiliations":[{"raw_affiliation_string":"Computer Science, POSTECH, Korea","institution_ids":["https://openalex.org/I2799891827","https://openalex.org/I123900574"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5020055570"],"corresponding_institution_ids":["https://openalex.org/I123900574","https://openalex.org/I2799891827"],"apc_list":null,"apc_paid":null,"fwci":1.3529,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.8239333,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"45","issue":"7","first_page":"1","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998000264167786,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998000264167786,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.996999979019165,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7604312896728516},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7002590298652649},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6777252554893494},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6716863512992859},{"id":"https://openalex.org/keywords/hough-transform","display_name":"Hough transform","score":0.6567668318748474},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6211455464363098},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.619449257850647},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5231115221977234},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.43708425760269165},{"id":"https://openalex.org/keywords/scale-invariant-feature-transform","display_name":"Scale-invariant feature transform","score":0.4206793010234833},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3747330605983734},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21956509351730347},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1843472719192505}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7604312896728516},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7002590298652649},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6777252554893494},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6716863512992859},{"id":"https://openalex.org/C200518788","wikidata":"https://www.wikidata.org/wiki/Q195076","display_name":"Hough transform","level":3,"score":0.6567668318748474},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6211455464363098},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.619449257850647},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5231115221977234},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43708425760269165},{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.4206793010234833},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3747330605983734},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21956509351730347},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1843472719192505},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2022.3233884","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3233884","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:37018584","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37018584","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":108,"referenced_works":["https://openalex.org/W22745672","https://openalex.org/W209424029","https://openalex.org/W764651262","https://openalex.org/W1522301498","https://openalex.org/W1556531089","https://openalex.org/W1576725826","https://openalex.org/W1587878450","https://openalex.org/W1677409904","https://openalex.org/W1686810756","https://openalex.org/W1727982597","https://openalex.org/W1896794744","https://openalex.org/W1901129140","https://openalex.org/W1919709169","https://openalex.org/W1981857004","https://openalex.org/W1996901117","https://openalex.org/W2011891945","https://openalex.org/W2085261163","https://openalex.org/W2090518410","https://openalex.org/W2100029819","https://openalex.org/W2103375950","https://openalex.org/W2108598243","https://openalex.org/W2113226010","https://openalex.org/W2124861766","https://openalex.org/W2125434107","https://openalex.org/W2128974588","https://openalex.org/W2129662884","https://openalex.org/W2135931458","https://openalex.org/W2142726150","https://openalex.org/W2149259880","https://openalex.org/W2151103935","https://openalex.org/W2161969291","https://openalex.org/W2163605009","https://openalex.org/W2163819245","https://openalex.org/W2194775991","https://openalex.org/W2197504061","https://openalex.org/W2292862470","https://openalex.org/W2460371498","https://openalex.org/W2464606141","https://openalex.org/W2488101876","https://openalex.org/W2531409750","https://openalex.org/W2533007775","https://openalex.org/W2604233003","https://openalex.org/W2604881841","https://openalex.org/W2736876108","https://openalex.org/W2752782242","https://openalex.org/W2754925132","https://openalex.org/W2771418247","https://openalex.org/W2884131745","https://openalex.org/W2885650013","https://openalex.org/W2886782161","https://openalex.org/W2891202958","https://openalex.org/W2950974964","https://openalex.org/W2963020784","https://openalex.org/W2963048316","https://openalex.org/W2963125010","https://openalex.org/W2963163009","https://openalex.org/W2963325280","https://openalex.org/W2963446712","https://openalex.org/W2963827464","https://openalex.org/W2963881378","https://openalex.org/W2964188292","https://openalex.org/W2964700958","https://openalex.org/W2970350341","https://openalex.org/W2971252756","https://openalex.org/W2981995220","https://openalex.org/W2982121679","https://openalex.org/W2985822417","https://openalex.org/W2988715931","https://openalex.org/W3035242260","https://openalex.org/W3035472788","https://openalex.org/W3035477606","https://openalex.org/W3035578028","https://openalex.org/W3092135995","https://openalex.org/W3095145867","https://openalex.org/W3099546855","https://openalex.org/W3104213423","https://openalex.org/W3106982106","https://openalex.org/W3149878926","https://openalex.org/W3164763551","https://openalex.org/W3169596906","https://openalex.org/W3174012569","https://openalex.org/W3181461461","https://openalex.org/W4205425515","https://openalex.org/W4251485470","https://openalex.org/W4287900618","https://openalex.org/W4295312788","https://openalex.org/W4297775537","https://openalex.org/W4387928059","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6637400245","https://openalex.org/W6639685146","https://openalex.org/W6639824700","https://openalex.org/W6675352095","https://openalex.org/W6676923985","https://openalex.org/W6679667936","https://openalex.org/W6684191040","https://openalex.org/W6737664043","https://openalex.org/W6754783729","https://openalex.org/W6754984195","https://openalex.org/W6764386301","https://openalex.org/W6766978945","https://openalex.org/W6767840039","https://openalex.org/W6768009244","https://openalex.org/W6771376659","https://openalex.org/W6779835006","https://openalex.org/W6793652844","https://openalex.org/W6797170341"],"related_works":["https://openalex.org/W3034955165","https://openalex.org/W2030098947","https://openalex.org/W2094920358","https://openalex.org/W2041448692","https://openalex.org/W1974777989","https://openalex.org/W2363834444","https://openalex.org/W2247121321","https://openalex.org/W2003466055","https://openalex.org/W2070077862","https://openalex.org/W2049930962"],"abstract_inverted_index":{"Despite":[0],"advances":[1],"in":[2,59,134],"feature":[3],"representation,":[4],"leveraging":[5],"geometric":[6,36,53],"relations":[7],"is":[8],"crucial":[9],"for":[10,153],"establishing":[11],"reliable":[12],"visual":[13,155],"correspondences":[14],"under":[15],"large":[16],"variations":[17],"of":[18,48,84,92,137,147],"images.":[19],"In":[20],"this":[21],"work":[22],"we":[23,95,122],"introduce":[24],"a":[25,52,60,67,72,81,144],"Hough":[26,41],"transform":[27],"perspective":[28],"on":[29,150],"convolutional":[30,61,132],"matching":[31,37,79,133],"and":[32,56,139],"propose":[33,97],"an":[34,100],"effective":[35],"algorithm,":[38],"dubbed":[39],"Convolutional":[40],"Matching":[42],"(CHM).":[43],"The":[44],"method":[45,142],"distributes":[46],"similarities":[47],"candidate":[49],"matches":[50],"over":[51],"transformation":[54],"space":[55,136],"evaluates":[57],"them":[58],"manner.":[62],"We":[63],"cast":[64],"it":[65],"into":[66],"trainable":[68],"neural":[69,125],"layer":[70],"with":[71,80,104,127],"semi-isotropic":[73,112],"high-dimensional":[74,93],"kernel,":[75],"which":[76,107],"learns":[77],"non-rigid":[78],"small":[82],"number":[83],"interpretable":[85],"parameters.":[86],"To":[87,117],"further":[88],"improve":[89],"the":[90,110,119,124,135,148],"efficiency":[91],"voting,":[94],"also":[96],"to":[98,161],"use":[99],"efficient":[101],"kernel":[102],"decomposition":[103],"center-pivot":[105],"neighbors,":[106],"significantly":[108],"sparsifies":[109],"proposed":[111,120],"kernels":[113],"without":[114],"performance":[115],"degradation.":[116],"validate":[118],"techniques,":[121],"develop":[123],"network":[126],"CHM":[128],"layers":[129],"that":[130],"perform":[131],"translation":[138],"scaling.":[140],"Our":[141],"sets":[143],"new":[145],"state":[146],"art":[149],"standard":[151],"benchmarks":[152],"semantic":[154],"correspondence,":[156],"proving":[157],"its":[158],"strong":[159],"robustness":[160],"challenging":[162],"intra-class":[163],"variations.":[164]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4}],"updated_date":"2026-02-25T08:12:03.925757","created_date":"2025-10-10T00:00:00"}
