{"id":"https://openalex.org/W1938890191","doi":"https://doi.org/10.1109/cvpr.2015.7299164","title":"A flexible tensor block coordinate ascent scheme for hypergraph matching","display_name":"A flexible tensor block coordinate ascent scheme for hypergraph matching","publication_year":2015,"publication_date":"2015-06-01","ids":{"openalex":"https://openalex.org/W1938890191","doi":"https://doi.org/10.1109/cvpr.2015.7299164","mag":"1938890191"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2015.7299164","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2015.7299164","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-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/A5108380784","display_name":"Quynh Nguyen Ngoc","orcid":null},"institutions":[{"id":"https://openalex.org/I4210109712","display_name":"Max Planck Institute for Informatics","ror":"https://ror.org/01w19ak89","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210109712"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Quynh Nguyen Ngoc","raw_affiliation_strings":["Max Planck Institute for Informatics, Saarbr\u00fccken, Germany","Max Planck Institute for informatics, Saarbr\u00fccken, Germany"],"affiliations":[{"raw_affiliation_string":"Max Planck Institute for Informatics, Saarbr\u00fccken, Germany","institution_ids":["https://openalex.org/I4210109712"]},{"raw_affiliation_string":"Max Planck Institute for informatics, Saarbr\u00fccken, Germany","institution_ids":["https://openalex.org/I4210109712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108248868","display_name":"Antoine Gautier","orcid":null},"institutions":[{"id":"https://openalex.org/I91712215","display_name":"Saarland University","ror":"https://ror.org/01jdpyv68","country_code":"DE","type":"education","lineage":["https://openalex.org/I91712215"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Antoine Gautier","raw_affiliation_strings":["Saarland University, Saarbr\u00fccken, Germany","Saarland Univ., Saarbr\u00fccken, Germany#TAB#"],"affiliations":[{"raw_affiliation_string":"Saarland University, Saarbr\u00fccken, Germany","institution_ids":["https://openalex.org/I91712215"]},{"raw_affiliation_string":"Saarland Univ., Saarbr\u00fccken, Germany#TAB#","institution_ids":["https://openalex.org/I91712215"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025830560","display_name":"Matthias Hein","orcid":"https://orcid.org/0000-0002-8751-7760"},"institutions":[{"id":"https://openalex.org/I91712215","display_name":"Saarland University","ror":"https://ror.org/01jdpyv68","country_code":"DE","type":"education","lineage":["https://openalex.org/I91712215"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Matthias Hein","raw_affiliation_strings":["Saarland University, Saarbr\u00fccken, Germany","Saarland Univ., Saarbr\u00fccken, Germany#TAB#"],"affiliations":[{"raw_affiliation_string":"Saarland University, Saarbr\u00fccken, Germany","institution_ids":["https://openalex.org/I91712215"]},{"raw_affiliation_string":"Saarland Univ., Saarbr\u00fccken, Germany#TAB#","institution_ids":["https://openalex.org/I91712215"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5108380784"],"corresponding_institution_ids":["https://openalex.org/I4210109712"],"apc_list":null,"apc_paid":null,"fwci":4.4923,"has_fulltext":false,"cited_by_count":51,"citation_normalized_percentile":{"value":0.96397787,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"5270","last_page":"5278"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":1.0,"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/T12292","display_name":"Graph Theory and Algorithms","score":1.0,"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/T11106","display_name":"Data Management and Algorithms","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10720","display_name":"Complexity and Algorithms in Graphs","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/hypergraph","display_name":"Hypergraph","score":0.7675800323486328},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6986730694770813},{"id":"https://openalex.org/keywords/3-dimensional-matching","display_name":"3-dimensional matching","score":0.6517248749732971},{"id":"https://openalex.org/keywords/bipartite-graph","display_name":"Bipartite graph","score":0.607226550579071},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.571452260017395},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5076020956039429},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4929654598236084},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4766429364681244},{"id":"https://openalex.org/keywords/assignment-problem","display_name":"Assignment problem","score":0.4707396924495697},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.46675753593444824},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.45341572165489197},{"id":"https://openalex.org/keywords/monotonic-function","display_name":"Monotonic function","score":0.4319309592247009},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.42193999886512756},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34691715240478516},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3253413438796997},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.32045114040374756},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26887935400009155},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.1613798439502716},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.13229691982269287}],"concepts":[{"id":"https://openalex.org/C2781221856","wikidata":"https://www.wikidata.org/wiki/Q840247","display_name":"Hypergraph","level":2,"score":0.7675800323486328},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6986730694770813},{"id":"https://openalex.org/C72545166","wikidata":"https://www.wikidata.org/wiki/Q10866593","display_name":"3-dimensional matching","level":4,"score":0.6517248749732971},{"id":"https://openalex.org/C197657726","wikidata":"https://www.wikidata.org/wiki/Q174733","display_name":"Bipartite graph","level":3,"score":0.607226550579071},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.571452260017395},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5076020956039429},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4929654598236084},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4766429364681244},{"id":"https://openalex.org/C85044808","wikidata":"https://www.wikidata.org/wiki/Q620614","display_name":"Assignment problem","level":2,"score":0.4707396924495697},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.46675753593444824},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.45341572165489197},{"id":"https://openalex.org/C72169020","wikidata":"https://www.wikidata.org/wiki/Q194404","display_name":"Monotonic function","level":2,"score":0.4319309592247009},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.42193999886512756},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34691715240478516},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3253413438796997},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.32045114040374756},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26887935400009155},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.1613798439502716},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.13229691982269287},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cvpr.2015.7299164","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2015.7299164","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.719.4085","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.719.4085","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ml.uni-saarland.de/Publications/NguGauHei-TensorBCAforHypergraphMatching.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1587878450","https://openalex.org/W1744214816","https://openalex.org/W1970279742","https://openalex.org/W1988650493","https://openalex.org/W1998840160","https://openalex.org/W2003296078","https://openalex.org/W2074078071","https://openalex.org/W2076080556","https://openalex.org/W2079272365","https://openalex.org/W2094539604","https://openalex.org/W2097784989","https://openalex.org/W2100187127","https://openalex.org/W2103375950","https://openalex.org/W2107855892","https://openalex.org/W2119309061","https://openalex.org/W2121225280","https://openalex.org/W2124386111","https://openalex.org/W2124465992","https://openalex.org/W2136425492","https://openalex.org/W2138910149","https://openalex.org/W2142726150","https://openalex.org/W2150760714","https://openalex.org/W2152953631","https://openalex.org/W2153396823","https://openalex.org/W2154583877","https://openalex.org/W2158256890","https://openalex.org/W2166524953","https://openalex.org/W2166820607","https://openalex.org/W2222512263","https://openalex.org/W2467020497","https://openalex.org/W2476974423","https://openalex.org/W2964185177","https://openalex.org/W4293718195","https://openalex.org/W6635241246","https://openalex.org/W6637760914","https://openalex.org/W6669552665","https://openalex.org/W6675352095","https://openalex.org/W6676075050","https://openalex.org/W6677958503","https://openalex.org/W6680144647","https://openalex.org/W6682759379"],"related_works":["https://openalex.org/W2054458431","https://openalex.org/W2077309407","https://openalex.org/W3181584291","https://openalex.org/W2371352078","https://openalex.org/W4205756423","https://openalex.org/W2567825307","https://openalex.org/W2966673134","https://openalex.org/W2352066879","https://openalex.org/W1559931991","https://openalex.org/W2080136900"],"abstract_inverted_index":{"The":[0],"estimation":[1],"of":[2,67,72,110,120,139,161,166],"correspondences":[3],"between":[4],"two":[5,101],"images":[6],"resp.":[7],"point":[8],"sets":[9],"is":[10,23,33],"a":[11,55,87,158],"core":[12],"problem":[13,22,31,58],"in":[14,113,137,149],"computer":[15],"vision.":[16],"One":[17],"way":[18],"to":[19,27,44,54],"formulate":[20],"the":[21,28,108,114,118,125],"graph":[24],"matching":[25,52,115,142,145],"leading":[26,53],"quadratic":[29],"assignment":[30,122],"which":[32,103],"NP-hard.":[34],"Several":[35],"so":[36],"called":[37],"second":[38],"order":[39,57,75],"methods":[40,95],"have":[41],"been":[42],"proposed":[43],"solve":[45],"this":[46,83],"problem.":[47],"In":[48,82,124],"recent":[49],"years":[50],"hypergraph":[51,97],"third":[56,74],"became":[59],"popular":[60],"as":[61],"it":[62],"allows":[63],"for":[64,90,96,151],"better":[65,141],"integration":[66],"geometric":[68],"information.":[69],"For":[70],"most":[71],"these":[73],"algorithms":[76,102,132],"no":[77],"theoretical":[78],"guarantees":[79],"are":[80],"known.":[81],"paper":[84],"we":[85,127],"propose":[86,100],"general":[88],"framework":[89],"tensor":[91],"block":[92],"coordinate":[93],"ascent":[94,112],"matching.":[98],"We":[99],"both":[104,136],"come":[105],"along":[106],"with":[107],"guarantee":[109],"monotonic":[111],"score":[116],"on":[117],"set":[119],"discrete":[121],"matrices.":[123],"experiments":[126],"show":[128],"that":[129],"our":[130],"new":[131],"outperform":[133],"previous":[134],"work":[135],"terms":[138],"achieving":[140],"scores":[143],"and":[144,163],"accuracy.":[146],"This":[147],"holds":[148],"particular":[150],"very":[152],"challenging":[153],"settings":[154],"where":[155],"one":[156],"has":[157],"high":[159],"number":[160],"outliers":[162],"other":[164],"forms":[165],"noise.":[167]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":9},{"year":2016,"cited_by_count":9},{"year":2015,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
