{"id":"https://openalex.org/W4417427507","doi":"https://doi.org/10.1109/tpami.2025.3644296","title":"MESA: Effective Matching Redundancy Reduction by Semantic Area Segmentation","display_name":"MESA: Effective Matching Redundancy Reduction by Semantic Area Segmentation","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W4417427507","doi":"https://doi.org/10.1109/tpami.2025.3644296","pmid":"https://pubmed.ncbi.nlm.nih.gov/41396771"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2025.3644296","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2025.3644296","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":null,"display_name":"Yesheng Zhang","orcid":"https://orcid.org/0000-0001-8427-0654"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yesheng Zhang","raw_affiliation_strings":["School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-8427-0654","affiliations":[{"raw_affiliation_string":"School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055576241","display_name":"Shuhan Shen","orcid":"https://orcid.org/0000-0002-8704-7914"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuhan Shen","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-8704-7914","affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210094879","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":null,"display_name":"Xu Zhao","orcid":"https://orcid.org/0000-0002-8176-623X"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Zhao","raw_affiliation_strings":["School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-8176-623X","affiliations":[{"raw_affiliation_string":"School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.39863464,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"48","issue":"4","first_page":"4454","last_page":"4472"},"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":0.7828999757766724,"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":0.7828999757766724,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.06800000369548798,"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":0.060600001364946365,"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/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6122999787330627},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5867999792098999},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5679000020027161},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5568000078201294},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.4641999900341034},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.45329999923706055},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4383000135421753},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.43149998784065247},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.426800012588501}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7031000256538391},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6503999829292297},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6122999787330627},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5867999792098999},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5679000020027161},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5568000078201294},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.4641999900341034},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.45329999923706055},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4383000135421753},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.43149998784065247},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.426800012588501},{"id":"https://openalex.org/C5134670","wikidata":"https://www.wikidata.org/wiki/Q1626444","display_name":"Cut","level":4,"score":0.414000004529953},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.39570000767707825},{"id":"https://openalex.org/C158096908","wikidata":"https://www.wikidata.org/wiki/Q3983303","display_name":"Template matching","level":3,"score":0.3944000005722046},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.3806000053882599},{"id":"https://openalex.org/C200336642","wikidata":"https://www.wikidata.org/wiki/Q15058706","display_name":"Point set registration","level":3,"score":0.3596000075340271},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33709999918937683},{"id":"https://openalex.org/C2983787585","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature matching","level":3,"score":0.3345000147819519},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.3294999897480011},{"id":"https://openalex.org/C72545166","wikidata":"https://www.wikidata.org/wiki/Q10866593","display_name":"3-dimensional matching","level":4,"score":0.3240000009536743},{"id":"https://openalex.org/C2986492983","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image matching","level":3,"score":0.3151000142097473},{"id":"https://openalex.org/C61455927","wikidata":"https://www.wikidata.org/wiki/Q1030529","display_name":"Blossom algorithm","level":3,"score":0.30300000309944153},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.2962999939918518},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.2833000123500824},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.2831999957561493},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.2759000062942505},{"id":"https://openalex.org/C14961307","wikidata":"https://www.wikidata.org/wiki/Q5377176","display_name":"Energy minimization","level":2,"score":0.2732999920845032},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.26899999380111694},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.25209999084472656},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2517000138759613}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2025.3644296","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2025.3644296","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:41396771","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41396771","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":[{"id":"https://openalex.org/G768824778","display_name":null,"funder_award_id":"62176156","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W1245714593","https://openalex.org/W1965511886","https://openalex.org/W2085261163","https://openalex.org/W2085905957","https://openalex.org/W2101309634","https://openalex.org/W2117228865","https://openalex.org/W2143516773","https://openalex.org/W2151103935","https://openalex.org/W2250384498","https://openalex.org/W2471962767","https://openalex.org/W2490662969","https://openalex.org/W2504335775","https://openalex.org/W2564084673","https://openalex.org/W2594519801","https://openalex.org/W2802772536","https://openalex.org/W2897085414","https://openalex.org/W2951730755","https://openalex.org/W2962705366","https://openalex.org/W2963760790","https://openalex.org/W2964015640","https://openalex.org/W2979458572","https://openalex.org/W2990655570","https://openalex.org/W3009931536","https://openalex.org/W3034275286","https://openalex.org/W3034373437","https://openalex.org/W3043075211","https://openalex.org/W3043971245","https://openalex.org/W3047057232","https://openalex.org/W3096609285","https://openalex.org/W3166285241","https://openalex.org/W3176602998","https://openalex.org/W3203518786","https://openalex.org/W4200629514","https://openalex.org/W4221150397","https://openalex.org/W4285784610","https://openalex.org/W4312525925","https://openalex.org/W4312548398","https://openalex.org/W4381716329","https://openalex.org/W4382458246","https://openalex.org/W4385245566","https://openalex.org/W4386071759","https://openalex.org/W4386075582","https://openalex.org/W4386083040","https://openalex.org/W4388979610","https://openalex.org/W4390872507","https://openalex.org/W4390874369","https://openalex.org/W4390874575","https://openalex.org/W4391109864","https://openalex.org/W4401413596","https://openalex.org/W4402753858","https://openalex.org/W4402771002","https://openalex.org/W4402772491","https://openalex.org/W4402816534","https://openalex.org/W4403780865","https://openalex.org/W4404002617","https://openalex.org/W4404782324"],"related_works":[],"abstract_inverted_index":{"Matching":[0],"redundancy,":[1,35],"which":[2],"refers":[3],"to":[4,23,51,57,180],"fine-grained":[5],"feature":[6,18,69],"comparison":[7],"between":[8],"irrelevant":[9],"image":[10,44,233],"areas,":[11],"is":[12,110],"a":[13,79,86,100,113],"prevalent":[14],"limitation":[15],"in":[16,220],"current":[17],"matching":[19,30,34,81,107,130,134,172,219],"approaches.":[20],"It":[21],"leads":[22],"unnecessary":[24],"and":[25,39,117,158,201,229],"error-prone":[26],"computations,":[27],"ultimately":[28],"diminishing":[29],"accuracy.":[31,185],"To":[32],"reduce":[33],"we":[36],"propose":[37],"MESA":[38,77],"DMESA,":[40],"both":[41,199],"leveraging":[42],"advanced":[43],"understanding":[45],"of":[46,90,175,217],"Segment":[47],"Anything":[48],"Model":[49],"(SAM)":[50],"establish":[52],"semantic":[53],"area":[54,62,129,171],"matches":[55],"prior":[56],"point":[58,74,218],"matching.":[59,75],"These":[60],"informative":[61],"matches,":[63],"then,":[64],"can":[65],"undergo":[66],"effective":[67],"internal":[68],"comparison,":[70],"facilitating":[71],"precise":[72],"inside-area":[73],"Specifically,":[76],"adopts":[78],"sparse":[80],"framework,":[82],"while":[83,182],"DMESA":[84,127,168],"applies":[85],"dense":[87,133],"one.":[88],"Both":[89],"them":[91],"first":[92],"obtain":[93],"candidate":[94],"areas":[95],"from":[96,123,148],"SAM":[97],"results":[98,205],"through":[99],"novel":[101],"Area":[102],"Graph":[103],"(AG).":[104],"In":[105,125],"MESA,":[106,181],"the":[108,137,154,161],"candidates":[109],"formulated":[111],"as":[112,153],"graph":[114],"energy":[115],"minimization":[116],"solved":[118],"by":[119,131],"graphical":[120],"models":[121],"derived":[122],"AG.":[124],"contrast,":[126],"performs":[128],"generating":[132],"distributions":[135,145],"on":[136,191],"entire":[138],"image,":[139],"aiming":[140],"at":[141],"enhancing":[142],"efficiency.":[143],"The":[144,204],"are":[146,188],"produced":[147],"off-the-shelf":[149],"patch":[150],"matching,":[151],"modeled":[152],"Gaussian":[155],"Mixture":[156],"Model,":[157],"refined":[159],"via":[160],"Expectation":[162],"Maximization.":[163],"With":[164],"less":[165],"repetitive":[166],"computation,":[167],"showcases":[169],"an":[170],"speed":[173],"improvement":[174],"nearly":[176],"five":[177],"times":[178],"compared":[179],"maintaining":[183],"competitive":[184],"Our":[186],"methods":[187,225],"extensively":[189],"evaluated":[190],"four":[192],"different":[193],"tasks":[194],"across":[195],"six":[196],"datasets,":[197],"encompassing":[198],"indoor":[200],"outdoor":[202],"scenes.":[203],"suggest":[206],"that":[207],"our":[208,224],"method":[209],"achieves":[210],"notable":[211],"accuracy":[212],"improvements":[213],"for":[214],"nine":[215],"baselines":[216],"most":[221],"cases.":[222],"Furthermore,":[223],"exhibit":[226],"promise":[227],"generalization":[228],"improved":[230],"robustness":[231],"against":[232],"resolution.":[234]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-12-15T00:00:00"}