{"id":"https://openalex.org/W2075110006","doi":"https://doi.org/10.1109/cvpr.2012.6248035","title":"Leveraging category-level labels for instance-level image retrieval","display_name":"Leveraging category-level labels for instance-level image retrieval","publication_year":2012,"publication_date":"2012-06-01","ids":{"openalex":"https://openalex.org/W2075110006","doi":"https://doi.org/10.1109/cvpr.2012.6248035","mag":"2075110006"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2012.6248035","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2012.6248035","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Conference on Computer Vision and Pattern Recognition","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/A5055317342","display_name":"Ana Gordoa","orcid":"https://orcid.org/0000-0003-1822-8196"},"institutions":[{"id":"https://openalex.org/I123044942","display_name":"Universitat Aut\u00f2noma de Barcelona","ror":"https://ror.org/052g8jq94","country_code":"ES","type":"education","lineage":["https://openalex.org/I123044942"]},{"id":"https://openalex.org/I33976269","display_name":"Xerox (France)","ror":"https://ror.org/033q0mv79","country_code":"FR","type":"company","lineage":["https://openalex.org/I33976269","https://openalex.org/I4210132870"]}],"countries":["ES","FR"],"is_corresponding":true,"raw_author_name":"A. Gordoa","raw_affiliation_strings":["Computer Vision Center, Universitat Aut\u00f2noma de Barcelona, Spain","Textual and Visual Pattern Analysis, Xerox Research Center Europe, France"],"affiliations":[{"raw_affiliation_string":"Computer Vision Center, Universitat Aut\u00f2noma de Barcelona, Spain","institution_ids":["https://openalex.org/I123044942"]},{"raw_affiliation_string":"Textual and Visual Pattern Analysis, Xerox Research Center Europe, France","institution_ids":["https://openalex.org/I33976269"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028150113","display_name":"Jos\u00e9 A. Rodr\u00edguez-Serrano","orcid":"https://orcid.org/0009-0005-0239-8117"},"institutions":[{"id":"https://openalex.org/I33976269","display_name":"Xerox (France)","ror":"https://ror.org/033q0mv79","country_code":"FR","type":"company","lineage":["https://openalex.org/I33976269","https://openalex.org/I4210132870"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"J. A. Rodriguez-Serrano","raw_affiliation_strings":["Textual and Visual Pattern Analysis, Xerox Research Center Europe, France"],"affiliations":[{"raw_affiliation_string":"Textual and Visual Pattern Analysis, Xerox Research Center Europe, France","institution_ids":["https://openalex.org/I33976269"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014589088","display_name":"F. Perronnin","orcid":null},"institutions":[{"id":"https://openalex.org/I33976269","display_name":"Xerox (France)","ror":"https://ror.org/033q0mv79","country_code":"FR","type":"company","lineage":["https://openalex.org/I33976269","https://openalex.org/I4210132870"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"F. Perronnin","raw_affiliation_strings":["Textual and Visual Pattern Analysis, Xerox Research Center Europe, France"],"affiliations":[{"raw_affiliation_string":"Textual and Visual Pattern Analysis, Xerox Research Center Europe, France","institution_ids":["https://openalex.org/I33976269"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003047329","display_name":"Ernest Valveny","orcid":"https://orcid.org/0000-0002-0368-9697"},"institutions":[{"id":"https://openalex.org/I123044942","display_name":"Universitat Aut\u00f2noma de Barcelona","ror":"https://ror.org/052g8jq94","country_code":"ES","type":"education","lineage":["https://openalex.org/I123044942"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"E. Valveny","raw_affiliation_strings":["Computer Vision Center, Universitat Aut\u00f2noma de Barcelona, Spain"],"affiliations":[{"raw_affiliation_string":"Computer Vision Center, Universitat Aut\u00f2noma de Barcelona, Spain","institution_ids":["https://openalex.org/I123044942"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5055317342"],"corresponding_institution_ids":["https://openalex.org/I123044942","https://openalex.org/I33976269"],"apc_list":null,"apc_paid":null,"fwci":10.1583,"has_fulltext":false,"cited_by_count":73,"citation_normalized_percentile":{"value":0.98605566,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3045","last_page":"3052"},"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":0.9993000030517578,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9764999747276306,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/subspace-topology","display_name":"Subspace topology","score":0.6840659976005554},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6797047853469849},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.659858226776123},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.6442189812660217},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6083352565765381},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5820920467376709},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5496672987937927},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.47405192255973816},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.44420522451400757},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.43688973784446716},{"id":"https://openalex.org/keywords/canonical-correlation","display_name":"Canonical correlation","score":0.43397796154022217},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.41919952630996704},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4147830903530121},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3820376396179199}],"concepts":[{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.6840659976005554},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6797047853469849},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.659858226776123},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.6442189812660217},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6083352565765381},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5820920467376709},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5496672987937927},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.47405192255973816},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.44420522451400757},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.43688973784446716},{"id":"https://openalex.org/C153874254","wikidata":"https://www.wikidata.org/wiki/Q115542","display_name":"Canonical correlation","level":2,"score":0.43397796154022217},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.41919952630996704},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4147830903530121},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3820376396179199},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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/cvpr.2012.6248035","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2012.6248035","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1556531089","https://openalex.org/W1566135517","https://openalex.org/W1606858007","https://openalex.org/W1972378554","https://openalex.org/W1978962787","https://openalex.org/W1988511239","https://openalex.org/W2003558525","https://openalex.org/W2006493005","https://openalex.org/W2012592962","https://openalex.org/W2012833704","https://openalex.org/W2025341678","https://openalex.org/W2047221353","https://openalex.org/W2071027807","https://openalex.org/W2074668987","https://openalex.org/W2084363474","https://openalex.org/W2090923791","https://openalex.org/W2102765684","https://openalex.org/W2106053110","https://openalex.org/W2108598243","https://openalex.org/W2122528955","https://openalex.org/W2123576058","https://openalex.org/W2124509324","https://openalex.org/W2125378448","https://openalex.org/W2128017662","https://openalex.org/W2129921015","https://openalex.org/W2131627887","https://openalex.org/W2131846894","https://openalex.org/W2147238549","https://openalex.org/W2147717514","https://openalex.org/W2151103935","https://openalex.org/W2151509460","https://openalex.org/W2168371480","https://openalex.org/W2169495281","https://openalex.org/W2293597654","https://openalex.org/W2543453567","https://openalex.org/W2543932557","https://openalex.org/W3143107425","https://openalex.org/W3145063618","https://openalex.org/W4230940751","https://openalex.org/W4237723258","https://openalex.org/W6636412649","https://openalex.org/W6652007689","https://openalex.org/W6675751002","https://openalex.org/W6676297131","https://openalex.org/W6678145947","https://openalex.org/W6678556256","https://openalex.org/W6679620863","https://openalex.org/W6697214482","https://openalex.org/W6729029445","https://openalex.org/W6818868544"],"related_works":["https://openalex.org/W2123957576","https://openalex.org/W1995622179","https://openalex.org/W1484111231","https://openalex.org/W3125756894","https://openalex.org/W1552543208","https://openalex.org/W2074396517","https://openalex.org/W2166963679","https://openalex.org/W2187269125","https://openalex.org/W1641615907","https://openalex.org/W2059785080"],"abstract_inverted_index":{"In":[0,156],"this":[1,52,82,154],"article,":[2],"we":[3,84,141,143,159,212],"focus":[4],"on":[5,95,103,109,118,172,214],"the":[6,67,90,100,106,115,126,134,137,145,149,179,233],"problem":[7],"of":[8,35,151,165,181],"large-scale":[9],"instance-level":[10],"image":[11,22,138],"retrieval.":[12],"For":[13],"efficiency":[14],"reasons,":[15],"it":[16],"is":[17,28,54,93,229],"common":[18],"to":[19,55,75,136,147,196,205,222,231],"represent":[20],"an":[21,44,210,216],"by":[23],"a":[24,32,57,61,78,96,163],"fixed-length":[25],"descriptor":[26],"which":[27],"subsequently":[29],"encoded":[30],"into":[31],"small":[33],"number":[34],"bits.":[36],"We":[37,64],"note":[38],"that":[39,188],"most":[40],"encoding":[41],"techniques":[42],"include":[43],"unsupervised":[45],"dimensionality":[46],"reduction":[47],"step.":[48],"Our":[49,184],"goal":[50],"in":[51,60,133,153,200,218],"work":[53],"learn":[56,76],"better":[58],"subspace":[59],"supervised":[62],"manner.":[63],"especially":[65],"raise":[66],"following":[68],"question:":[69],"\"can":[70],"category-level":[71,166],"labels":[72,167],"be":[73],"used":[74],"such":[77],"subspace?\"":[79],"To":[80],"answer":[81],"question,":[83],"experiment":[85],"with":[86,224],"four":[87],"learning":[88,98,190],"techniques:":[89],"first":[91,127,146],"one":[92,102,108,117],"based":[94],"metric":[97,189],"framework,":[99],"second":[101],"attribute":[104],"representations,":[105],"third":[107],"Canonical":[110],"Correlation":[111],"Analysis":[112],"(CCA)":[113],"and":[114,121,168,178,191,207],"fourth":[116],"Joint":[119],"Subspace":[120],"Classifier":[122],"Learning":[123],"(JSCL).":[124],"While":[125],"three":[128],"approaches":[129],"have":[130],"been":[131],"applied":[132],"past":[135],"retrieval":[139,170,201],"problem,":[140],"believe":[142],"are":[144],"show":[148],"usefulness":[150],"JSCL":[152,228],"context.":[155],"our":[157],"experiments,":[158],"use":[160],"ImageNet":[161],"as":[162,203],"source":[164],"report":[169,213],"results":[171],"two":[173],"standard":[174],"dataseis:":[175],"INRIA":[176],"Holidays":[177,215],"University":[180],"Kentucky":[182],"benchmark.":[183],"experimental":[185],"study":[186],"shows":[187],"attributes":[192],"do":[193],"not":[194],"lead":[195],"any":[197],"significant":[198],"improvement":[199],"accuracy,":[202],"opposed":[204],"CCA":[206],"JSCL.":[208],"As":[209],"example,":[211],"increase":[217],"accuracy":[219],"from":[220],"39.3%":[221],"48.6%":[223],"32-dimensional":[225],"representations.":[226],"Overall":[227],"shown":[230],"yield":[232],"best":[234],"results.":[235]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":10},{"year":2015,"cited_by_count":18},{"year":2014,"cited_by_count":11},{"year":2013,"cited_by_count":8}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}