{"id":"https://openalex.org/W1917730284","doi":"https://doi.org/10.1109/cvpr.2015.7298908","title":"Unsupervised visual alignment with similarity graphs","display_name":"Unsupervised visual alignment with similarity graphs","publication_year":2015,"publication_date":"2015-06-01","ids":{"openalex":"https://openalex.org/W1917730284","doi":"https://doi.org/10.1109/cvpr.2015.7298908","mag":"1917730284"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2015.7298908","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2015.7298908","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/A5019131343","display_name":"Fatemeh Shokrollahi Yancheshmeh","orcid":null},"institutions":[{"id":"https://openalex.org/I4210133110","display_name":"Tampere University","ror":null,"country_code":"FI","type":null,"lineage":["https://openalex.org/I4210133110"]},{"id":"https://openalex.org/I166825849","display_name":"Tampere University","ror":"https://ror.org/033003e23","country_code":"FI","type":"education","lineage":["https://openalex.org/I166825849"]}],"countries":["FI"],"is_corresponding":true,"raw_author_name":"Fatemeh Shokrollahi Yancheshmeh","raw_affiliation_strings":["Department of Signal Processing, Tampere University of Technology, Finland","Department of Signal Processing Tampere University of Technology, Finland"],"affiliations":[{"raw_affiliation_string":"Department of Signal Processing, Tampere University of Technology, Finland","institution_ids":["https://openalex.org/I166825849","https://openalex.org/I4210133110"]},{"raw_affiliation_string":"Department of Signal Processing Tampere University of Technology, Finland","institution_ids":["https://openalex.org/I4210133110"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100649535","display_name":"Ke Chen","orcid":"https://orcid.org/0000-0003-0928-5199"},"institutions":[{"id":"https://openalex.org/I166825849","display_name":"Tampere University","ror":"https://ror.org/033003e23","country_code":"FI","type":"education","lineage":["https://openalex.org/I166825849"]},{"id":"https://openalex.org/I4210133110","display_name":"Tampere University","ror":null,"country_code":"FI","type":null,"lineage":["https://openalex.org/I4210133110"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Ke Chen","raw_affiliation_strings":["Department of Signal Processing, Tampere University of Technology, Finland","Department of Signal Processing Tampere University of Technology, Finland"],"affiliations":[{"raw_affiliation_string":"Department of Signal Processing, Tampere University of Technology, Finland","institution_ids":["https://openalex.org/I166825849","https://openalex.org/I4210133110"]},{"raw_affiliation_string":"Department of Signal Processing Tampere University of Technology, Finland","institution_ids":["https://openalex.org/I4210133110"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054822570","display_name":"Joni\u2010Kristian K\u00e4m\u00e4r\u00e4inen","orcid":"https://orcid.org/0000-0002-5801-4371"},"institutions":[{"id":"https://openalex.org/I4210133110","display_name":"Tampere University","ror":null,"country_code":"FI","type":null,"lineage":["https://openalex.org/I4210133110"]},{"id":"https://openalex.org/I166825849","display_name":"Tampere University","ror":"https://ror.org/033003e23","country_code":"FI","type":"education","lineage":["https://openalex.org/I166825849"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Joni-Kristian Kamarainen","raw_affiliation_strings":["Department of Signal Processing, Tampere University of Technology, Finland","Department of Signal Processing Tampere University of Technology, Finland"],"affiliations":[{"raw_affiliation_string":"Department of Signal Processing, Tampere University of Technology, Finland","institution_ids":["https://openalex.org/I166825849","https://openalex.org/I4210133110"]},{"raw_affiliation_string":"Department of Signal Processing Tampere University of Technology, Finland","institution_ids":["https://openalex.org/I4210133110"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5019131343"],"corresponding_institution_ids":["https://openalex.org/I166825849","https://openalex.org/I4210133110"],"apc_list":null,"apc_paid":null,"fwci":1.4974,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.87940631,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"1","issue":null,"first_page":"2901","last_page":"2908"},"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":0.9987999796867371,"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":0.9987999796867371,"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":0.991599977016449,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9897000193595886,"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":0.7135598659515381},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5809386372566223},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5476013422012329},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3973623216152191},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.08851054310798645}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7135598659515381},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5809386372566223},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5476013422012329},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3973623216152191},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.08851054310798645}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cvpr.2015.7298908","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2015.7298908","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:10.1.1.909.6309","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.909.6309","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Yancheshmeh_Unsupervised_Visual_Alignment_2015_CVPR_paper.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321108","display_name":"Academy of Finland","ror":"https://ror.org/05k73zm37"},{"id":"https://openalex.org/F4320330293","display_name":"CSC \u2013 IT Center for Science","ror":"https://ror.org/04m8m1253"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W166750225","https://openalex.org/W1600222239","https://openalex.org/W1673923490","https://openalex.org/W1782590233","https://openalex.org/W1861492603","https://openalex.org/W1964062850","https://openalex.org/W1967072375","https://openalex.org/W1971937094","https://openalex.org/W1972515067","https://openalex.org/W1988324534","https://openalex.org/W1991264156","https://openalex.org/W1995543189","https://openalex.org/W2024047694","https://openalex.org/W2030536784","https://openalex.org/W2035652042","https://openalex.org/W2044520258","https://openalex.org/W2051506786","https://openalex.org/W2056944867","https://openalex.org/W2066941820","https://openalex.org/W2069916857","https://openalex.org/W2103956678","https://openalex.org/W2110070888","https://openalex.org/W2112378258","https://openalex.org/W2114113040","https://openalex.org/W2120419212","https://openalex.org/W2121532090","https://openalex.org/W2121721759","https://openalex.org/W2122888889","https://openalex.org/W2124386111","https://openalex.org/W2126060993","https://openalex.org/W2127453602","https://openalex.org/W2133774033","https://openalex.org/W2140363548","https://openalex.org/W2141362318","https://openalex.org/W2157285372","https://openalex.org/W2157558673","https://openalex.org/W2158760370","https://openalex.org/W2158844819","https://openalex.org/W2163605009","https://openalex.org/W2168002178","https://openalex.org/W2168356304","https://openalex.org/W2171074980","https://openalex.org/W2293657101","https://openalex.org/W2340149117","https://openalex.org/W2533113478","https://openalex.org/W2540396284","https://openalex.org/W2964153729","https://openalex.org/W3145128584","https://openalex.org/W4211015501","https://openalex.org/W4246219036","https://openalex.org/W4256379134","https://openalex.org/W4376522650","https://openalex.org/W6606767076","https://openalex.org/W6636091728","https://openalex.org/W6637162671","https://openalex.org/W6639102338","https://openalex.org/W6664702507","https://openalex.org/W6675876930","https://openalex.org/W6677963824","https://openalex.org/W6680786152","https://openalex.org/W6682865783","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Alignment":[0,73],"of":[1,18,74,101,112],"semantically":[2],"meaningful":[3],"visual":[4,75,137],"patterns,":[5],"such":[6,20],"as":[7,21,84],"object":[8,22],"classes,":[9],"is":[10,68,145,163],"an":[11,85,159,169],"important":[12],"pre-processing":[13],"step":[14],"for":[15,35,46],"a":[16,102,113,179],"number":[17],"applications":[19],"detection":[23],"and":[24,54,106,123,150],"image":[25,58,105,155,160,170],"categorization.":[26],"Considering":[27],"the":[28,33,92,108,132,140,191,197,201,207],"expensive":[29],"manpower":[30],"spent":[31],"on":[32],"annotation":[34],"supervised":[36],"alignment":[37,40],"methods,":[38,60],"unsupervised":[39,198],"techniques":[41],"are":[42],"more":[43],"favorable":[44],"especially":[45],"large-scale":[47],"problems.":[48],"Fine":[49],"adjustment":[50],"can":[51,90,116],"be":[52,117],"effectively":[53],"efficiently":[55],"achieved":[56],"with":[57,78,204],"congealing":[59],"but":[61,97],"they":[62],"require":[63,98],"moderately":[64],"good":[65,103],"initialization":[66],"which":[67,144,162,186],"largely":[69],"invalid":[70],"in":[71,125,190,196],"practice.":[72],"class":[76,115],"examples":[77,111],"large":[79],"view":[80],"point":[81],"changes":[82],"remains":[83],"open":[86],"problem.":[87],"Feature-based":[88],"methods":[89,203],"solve":[91],"problem":[93,143],"to":[94,165,171],"some":[95],"degree,":[96],"manual":[99],"selection":[100],"seed":[104,181],"omit":[107],"fact":[109],"that":[110],"semantic":[114],"visually":[118],"very":[119],"different":[120],"(e.g.,":[121],"Harley-Davidsons":[122],"Scooters":[124],"\u201cmotorbikes\u201d).":[126],"In":[127],"this":[128],"work,":[129],"we":[130,157],"overcome":[131],"aforementioned":[133],"drawbacks":[134],"by":[135,147,173,182],"defining":[136],"similarity":[138],"under":[139],"generalized":[141],"assignment":[142],"solved":[146],"fast":[148],"approximation":[149],"non-linear":[151],"optimization.":[152],"From":[153],"pair-wise":[154],"similarities":[156],"construct":[158],"graph":[161,174],"used":[164],"step-wise":[166],"align,":[167],"\u201cmorph\u201d,":[168],"another":[172],"traveling.":[175],"We":[176],"automatically":[177],"find":[178],"suitable":[180],"novel":[183],"centrality":[184],"measure":[185],"identifies":[187],"\u201csimilarity":[188],"hubs\u201d":[189],"graph.":[192],"The":[193],"proposed":[194],"approach":[195],"manner":[199],"outperforms":[200],"state-of-the-art":[202],"classes":[205],"from":[206],"popular":[208],"benchmark":[209],"datasets.":[210]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":3}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}