{"id":"https://openalex.org/W4313010934","doi":"https://doi.org/10.1109/cvpr52688.2022.00881","title":"Matching Feature Sets for Few-Shot Image Classification","display_name":"Matching Feature Sets for Few-Shot Image Classification","publication_year":2022,"publication_date":"2022-06-01","ids":{"openalex":"https://openalex.org/W4313010934","doi":"https://doi.org/10.1109/cvpr52688.2022.00881"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52688.2022.00881","pdf_url":null,"source":{"id":"https://openalex.org/S4363607701","display_name":"2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://arxiv.org/pdf/2204.00949","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5038710894","display_name":"Arman Afrasiyabi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Arman Afrasiyabi","raw_affiliation_strings":["Université Laval"],"affiliations":[{"raw_affiliation_string":"Université Laval","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019862529","display_name":"Hugo Larochelle","orcid":null},"institutions":[{"id":"https://openalex.org/I109736498","display_name":"Canadian Institute for Advanced Research","ror":"https://ror.org/01sdtdd95","country_code":"CA","type":"funder","lineage":["https://openalex.org/I109736498"]},{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"funder","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["CA","US"],"is_corresponding":false,"raw_author_name":"Hugo Larochelle","raw_affiliation_strings":["Canada CIFAR AI Chair","Google Brain"],"affiliations":[{"raw_affiliation_string":"Canada CIFAR AI Chair","institution_ids":["https://openalex.org/I109736498"]},{"raw_affiliation_string":"Google Brain","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034761030","display_name":"Jean\u2010Fran\u00e7ois Lalonde","orcid":"https://orcid.org/0000-0002-6583-2364"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jean-Francois Lalonde","raw_affiliation_strings":["Université Laval"],"affiliations":[{"raw_affiliation_string":"Université Laval","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045218915","display_name":"Christian Gagn\u00e9","orcid":"https://orcid.org/0000-0003-3697-4184"},"institutions":[{"id":"https://openalex.org/I109736498","display_name":"Canadian Institute for Advanced Research","ror":"https://ror.org/01sdtdd95","country_code":"CA","type":"funder","lineage":["https://openalex.org/I109736498"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Christian Gagne","raw_affiliation_strings":["Canada CIFAR AI Chair","Université Laval"],"affiliations":[{"raw_affiliation_string":"Canada CIFAR AI Chair","institution_ids":["https://openalex.org/I109736498"]},{"raw_affiliation_string":"Université Laval","institution_ids":[]}]}],"institution_assertions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":11.461,"has_fulltext":false,"cited_by_count":77,"citation_normalized_percentile":{"value":0.999893,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9998,"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"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9998,"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"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9963,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9851,"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/feature","display_name":"Feature (linguistics)","score":0.63581},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5617096},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5531814},{"id":"https://openalex.org/keywords/representation","display_name":"Representation","score":0.5526088}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.73512775},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7197989},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6622393},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.63581},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6156659},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.598982},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.58757293},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5617096},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5531814},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5531475},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5526088},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5513718},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.53906167},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.43966678},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.335235},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16681755},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52688.2022.00881","pdf_url":null,"source":{"id":"https://openalex.org/S4363607701","display_name":"2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2204.00949","pdf_url":"http://arxiv.org/pdf/2204.00949","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2204.00949","pdf_url":"http://arxiv.org/pdf/2204.00949","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.67}],"grants":[{"funder":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada","award_id":"RGPIN-2020-04799"}],"datasets":[],"versions":[],"referenced_works_count":73,"referenced_works":["https://openalex.org/W1797268635","https://openalex.org/W2154301842","https://openalex.org/W2162915993","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2565639579","https://openalex.org/W2589226201","https://openalex.org/W2601450892","https://openalex.org/W2604297385","https://openalex.org/W2604763608","https://openalex.org/W2753160622","https://openalex.org/W2765407302","https://openalex.org/W2787035179","https://openalex.org/W2791172704","https://openalex.org/W2796346823","https://openalex.org/W2798836702","https://openalex.org/W2805481182","https://openalex.org/W2808498263","https://openalex.org/W2909383239","https://openalex.org/W2950763986","https://openalex.org/W2962723986","https://openalex.org/W2962851944","https://openalex.org/W2962895018","https://openalex.org/W2962987395","https://openalex.org/W2963070905","https://openalex.org/W2963078860","https://openalex.org/W2963101867","https://openalex.org/W2963341924","https://openalex.org/W2963350370","https://openalex.org/W2963444553","https://openalex.org/W2963680240","https://openalex.org/W2963741406","https://openalex.org/W2963845150","https://openalex.org/W2963943197","https://openalex.org/W2964105864","https://openalex.org/W2964206659","https://openalex.org/W2965555521","https://openalex.org/W2967333288","https://openalex.org/W2979689312","https://openalex.org/W2980347982","https://openalex.org/W2981707695","https://openalex.org/W2982806777","https://openalex.org/W2988205463","https://openalex.org/W2994633389","https://openalex.org/W2995589713","https://openalex.org/W2998229299","https://openalex.org/W3001411605","https://openalex.org/W3012255272","https://openalex.org/W3034312118","https://openalex.org/W3034453888","https://openalex.org/W3035143213","https://openalex.org/W3081382462","https://openalex.org/W3094724482","https://openalex.org/W3096805028","https://openalex.org/W3104182862","https://openalex.org/W3109083691","https://openalex.org/W3122796902","https://openalex.org/W3123025241","https://openalex.org/W3127860328","https://openalex.org/W3139143706","https://openalex.org/W3181932393","https://openalex.org/W3182874523","https://openalex.org/W3194746126","https://openalex.org/W3195219609","https://openalex.org/W3205249428","https://openalex.org/W4214493665","https://openalex.org/W4214588794","https://openalex.org/W4244019866","https://openalex.org/W4288593364","https://openalex.org/W4293412117","https://openalex.org/W4300514939","https://openalex.org/W4300860215","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W4390516098","https://openalex.org/W4390143830","https://openalex.org/W4243199227","https://openalex.org/W4205302943","https://openalex.org/W3155418658","https://openalex.org/W2565656575","https://openalex.org/W2561132942","https://openalex.org/W2384362569","https://openalex.org/W2181948922","https://openalex.org/W2142795561"],"abstract_inverted_index":{"In":[0,28,172],"image":[1,143],"classification,":[2],"it":[3],"is":[4,139,153],"common":[5],"practice":[6],"to":[7,11,40,71,80,85,141],"train":[8],"deep":[9],"networks":[10],"extract":[12,41],"a":[13,52,57,135],"single":[14],"feature":[15,44,83,90],"vector":[16],"per":[17],"input":[18],"image.":[19,48],"Few-shot":[20],"classification":[21],"methods":[22],"also":[23],"mostly":[24],"follow":[25],"this":[26,29,34],"trend.":[27],"work,":[30],"we":[31,78],"depart":[32],"from":[33,62,92],"established":[35],"direction":[36],"and":[37,111,133,151,164,169],"instead":[38,86],"propose":[39,79],"sets":[42,88],"of":[43,60,89,125,147],"vectors":[45,91],"for":[46],"each":[47],"We":[49],"argue":[50],"that":[51,119],"set-based":[53],"representation":[54,59],"intrinsically":[55],"builds":[56],"richer":[58],"images":[61],"the":[63,72,122,167,180],"base":[64],"classes,":[65],"which":[66],"can":[67],"subsequently":[68],"better":[69],"transfer":[70],"few-shot":[73,160],"classes.":[74],"To":[75],"do":[76],"so,":[77],"adapt":[81],"existing":[82,103],"extractors":[84],"produce":[87],"images.":[93],"Our":[94],"approach,":[95],"dubbed":[96],"SetFeat,":[97],"embeds":[98],"shallow":[99],"self-attention":[100],"mechanisms":[101],"inside":[102],"encoder":[104],"architectures.":[105],"The":[106,145],"attention":[107],"modules":[108],"are":[109],"lightweight,":[110],"as":[112,127],"such":[113],"our":[114,148,177],"method":[115,178],"results":[116],"in":[117],"encoders":[118],"have":[120],"approximately":[121],"same":[123],"number":[124],"parameters":[126],"their":[128],"original":[129],"versions.":[130],"During":[131],"training":[132],"inference,":[134],"set-to-set":[136],"matching":[137],"metric":[138],"used":[140],"perform":[142],"classification.":[144],"effectiveness":[146],"proposed":[149],"architecture":[150],"metrics":[152],"demonstrated":[154],"via":[155],"thorough":[156],"experiments":[157],"on":[158],"standard":[159],"datasets-namely":[161],"miniImageNet,":[162],"tieredImageNet,":[163],"CUB-in":[165],"both":[166],"1-":[168],"5-shot":[170],"scenarios.":[171],"all":[173],"cases":[174],"but":[175],"one,":[176],"outperforms":[179],"state-of-the-art.":[181]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4313010934","counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":39},{"year":2023,"cited_by_count":29},{"year":2022,"cited_by_count":3}],"updated_date":"2025-02-25T02:34:23.132079","created_date":"2023-01-05"}