{"id":"https://openalex.org/W3181574378","doi":"https://doi.org/10.1109/cvprw53098.2021.00298","title":"Unlocking the Full Potential of Small Data with Diverse Supervision","display_name":"Unlocking the Full Potential of Small Data with Diverse Supervision","publication_year":2021,"publication_date":"2021-06-01","ids":{"openalex":"https://openalex.org/W3181574378","doi":"https://doi.org/10.1109/cvprw53098.2021.00298","mag":"3181574378"},"language":"en","primary_location":{"id":"doi:10.1109/cvprw53098.2021.00298","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw53098.2021.00298","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","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/A5074352142","display_name":"Ziqi Pang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ziqi Pang","raw_affiliation_strings":["TuSimple"],"affiliations":[{"raw_affiliation_string":"TuSimple","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071726426","display_name":"Zhiyuan Hu","orcid":"https://orcid.org/0000-0002-5865-1936"},"institutions":[{"id":"https://openalex.org/I4210140792","display_name":"Universidad Cat\u00f3lica Santo Domingo","ror":"https://ror.org/04ytq6y86","country_code":"DO","type":"education","lineage":["https://openalex.org/I4210140792"]}],"countries":["DO"],"is_corresponding":false,"raw_author_name":"Zhiyuan Hu","raw_affiliation_strings":["UCSD"],"affiliations":[{"raw_affiliation_string":"UCSD","institution_ids":["https://openalex.org/I4210140792"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040760890","display_name":"Pavel Tokmakov","orcid":"https://orcid.org/0000-0003-2043-6242"},"institutions":[{"id":"https://openalex.org/I4391768151","display_name":"Toyota Research Institute","ror":"https://ror.org/04fpkc108","country_code":null,"type":"facility","lineage":["https://openalex.org/I4210125472","https://openalex.org/I4391768151"]}],"countries":[],"is_corresponding":false,"raw_author_name":"Pavel Tokmakov","raw_affiliation_strings":["Toyota Research Institute"],"affiliations":[{"raw_affiliation_string":"Toyota Research Institute","institution_ids":["https://openalex.org/I4391768151"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102952938","display_name":"Yu-Xiong Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I308392441","display_name":"International University of the Caribbean","ror":"https://ror.org/02rv57d03","country_code":"JM","type":"education","lineage":["https://openalex.org/I308392441"]}],"countries":["JM"],"is_corresponding":false,"raw_author_name":"Yu-Xiong Wang","raw_affiliation_strings":["UIUC"],"affiliations":[{"raw_affiliation_string":"UIUC","institution_ids":["https://openalex.org/I308392441"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075246991","display_name":"Martial Hebert","orcid":"https://orcid.org/0000-0003-4566-5930"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Martial Hebert","raw_affiliation_strings":["CMU"],"affiliations":[{"raw_affiliation_string":"CMU","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5074352142"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.136,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.53514539,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"39","issue":null,"first_page":"2642","last_page":"2652"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9998999834060669,"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":0.9998999834060669,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9977999925613403,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9965000152587891,"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":0.8549131155014038},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6908968687057495},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5758465528488159},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5706313848495483},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5637195110321045},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.560985803604126},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.545066237449646},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5383437871932983},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.5374069809913635},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.5305168032646179},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5278772115707397},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.48401519656181335},{"id":"https://openalex.org/keywords/long-tail","display_name":"Long tail","score":0.46977633237838745},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.44471219182014465},{"id":"https://openalex.org/keywords/small-data","display_name":"Small data","score":0.4354058504104614},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.41333284974098206}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8549131155014038},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6908968687057495},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5758465528488159},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5706313848495483},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5637195110321045},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.560985803604126},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.545066237449646},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5383437871932983},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.5374069809913635},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.5305168032646179},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5278772115707397},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.48401519656181335},{"id":"https://openalex.org/C15189868","wikidata":"https://www.wikidata.org/wiki/Q534685","display_name":"Long tail","level":2,"score":0.46977633237838745},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.44471219182014465},{"id":"https://openalex.org/C2779280203","wikidata":"https://www.wikidata.org/wiki/Q17121211","display_name":"Small data","level":2,"score":0.4354058504104614},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.41333284974098206},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvprw53098.2021.00298","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw53098.2021.00298","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.699999988079071,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":105,"referenced_works":["https://openalex.org/W125693051","https://openalex.org/W179458199","https://openalex.org/W639708223","https://openalex.org/W1797268635","https://openalex.org/W1861492603","https://openalex.org/W1903029394","https://openalex.org/W2031489346","https://openalex.org/W2102605133","https://openalex.org/W2108598243","https://openalex.org/W2133013156","https://openalex.org/W2165644552","https://openalex.org/W2194321275","https://openalex.org/W2194775991","https://openalex.org/W2507296351","https://openalex.org/W2589226201","https://openalex.org/W2601450892","https://openalex.org/W2604763608","https://openalex.org/W2618530766","https://openalex.org/W2618799552","https://openalex.org/W2625674597","https://openalex.org/W2753160622","https://openalex.org/W2767434619","https://openalex.org/W2787035179","https://openalex.org/W2787501667","https://openalex.org/W2797977484","https://openalex.org/W2798441115","https://openalex.org/W2798836702","https://openalex.org/W2885201931","https://openalex.org/W2890538051","https://openalex.org/W2922482186","https://openalex.org/W2948171095","https://openalex.org/W2948672349","https://openalex.org/W2950673314","https://openalex.org/W2962723986","https://openalex.org/W2962743139","https://openalex.org/W2962843773","https://openalex.org/W2962864421","https://openalex.org/W2962933664","https://openalex.org/W2962945654","https://openalex.org/W2963070905","https://openalex.org/W2963078860","https://openalex.org/W2963101867","https://openalex.org/W2963150697","https://openalex.org/W2963211188","https://openalex.org/W2963341924","https://openalex.org/W2963498646","https://openalex.org/W2963677766","https://openalex.org/W2963741406","https://openalex.org/W2964105864","https://openalex.org/W2964112702","https://openalex.org/W2964250774","https://openalex.org/W2966262636","https://openalex.org/W2970941416","https://openalex.org/W2981468122","https://openalex.org/W2982152811","https://openalex.org/W2983166023","https://openalex.org/W2988205463","https://openalex.org/W2990873191","https://openalex.org/W2994633389","https://openalex.org/W2995253937","https://openalex.org/W2996623013","https://openalex.org/W3001411605","https://openalex.org/W3007429212","https://openalex.org/W3013629728","https://openalex.org/W3034672970","https://openalex.org/W3035524453","https://openalex.org/W3084193526","https://openalex.org/W3091905774","https://openalex.org/W3097337894","https://openalex.org/W3097571420","https://openalex.org/W3108975329","https://openalex.org/W3109083691","https://openalex.org/W3110608229","https://openalex.org/W4288335845","https://openalex.org/W4288573225","https://openalex.org/W6605121731","https://openalex.org/W6638319203","https://openalex.org/W6639102338","https://openalex.org/W6679564466","https://openalex.org/W6684671274","https://openalex.org/W6717697761","https://openalex.org/W6733532687","https://openalex.org/W6735236233","https://openalex.org/W6736057607","https://openalex.org/W6738045163","https://openalex.org/W6738279954","https://openalex.org/W6743661861","https://openalex.org/W6745995898","https://openalex.org/W6747943641","https://openalex.org/W6748284727","https://openalex.org/W6751281049","https://openalex.org/W6753311412","https://openalex.org/W6754005058","https://openalex.org/W6758126075","https://openalex.org/W6759807521","https://openalex.org/W6760378562","https://openalex.org/W6763070779","https://openalex.org/W6763320462","https://openalex.org/W6768806669","https://openalex.org/W6769623358","https://openalex.org/W6772329248","https://openalex.org/W6773502024","https://openalex.org/W6774285759","https://openalex.org/W6783045848","https://openalex.org/W6783596713"],"related_works":["https://openalex.org/W2786391746","https://openalex.org/W3132346564","https://openalex.org/W2991483587","https://openalex.org/W2914559142","https://openalex.org/W4226059458","https://openalex.org/W4381430104","https://openalex.org/W4361733581","https://openalex.org/W2995102745","https://openalex.org/W4286892028","https://openalex.org/W1540469842"],"abstract_inverted_index":{"Virtually":[0],"all":[1],"of":[2,10,13,21,30,49,90,190,200,219],"deep":[3],"learning":[4,23,149,158],"literature":[5],"relies":[6],"on":[7,26,142],"the":[8,19,57,87,97,114,134,146,153,160,169,188,198,207,225],"assumption":[9],"large":[11,28,47],"amounts":[12],"available":[14,234],"training":[15,191],"data.":[16],"Indeed,":[17],"even":[18,55],"majority":[20],"few-shot":[22,148],"methods":[24],"rely":[25],"a":[27,46,62,216],"set":[29,218],"\"base":[31],"classes\"":[32],"for":[33,101,156,163],"pre-training.":[34],"This":[35],"assumption,":[36],"however,":[37],"does":[38],"not":[39],"always":[40],"hold.":[41],"For":[42],"some":[43,65],"tasks,":[44,104],"annotating":[45],"number":[48],"classes":[50,155,162,192],"can":[51,60,221],"be":[52,61],"infeasible,":[53],"and":[54,74,139,159,172,183,193,231],"collecting":[56],"images":[58,173,220],"themselves":[59],"challenge":[63],"in":[64,80],"scenarios.":[66],"In":[67,110],"this":[68,72],"paper,":[69],"we":[70,93,112,151,166,180,196],"study":[71],"problem":[73],"call":[75,181],"it":[76],"\"Small":[77],"Data\"":[78],"setting,":[79],"contrast":[81],"to":[82,95,121,174,187],"\"Big":[83],"Data.\"":[84],"To":[85],"unlock":[86],"full":[88],"potential":[89],"small":[91,217,226],"data,":[92],"propose":[94],"augment":[96],"models":[98],"with":[99,127],"annotations":[100],"other":[102],"related":[103],"thus":[105],"increasing":[106],"their":[107,143],"generalization":[108],"abilities.":[109],"particular,":[111],"use":[113,152],"richly":[115],"annotated":[116],"scene":[117],"parsing":[118],"dataset":[119],"ADE20K":[120],"construct":[122],"our":[123],"realistic":[124],"Long-tail":[125],"Recognition":[126],"Diverse":[128],"Supervision":[129],"(LRDS)":[130],"benchmark,":[131],"by":[132],"splitting":[133],"object":[135],"categories":[136,171],"into":[137],"head":[138,154,170],"tail":[140,161],"based":[141],"distribution.":[144],"Following":[145],"standard":[147],"protocol,":[150],"representation":[157],"evaluation.":[164],"Moreover,":[165],"further":[167],"subsample":[168],"generate":[175],"two":[176],"novel":[177],"settings":[178],"which":[179],"\"Scarce-Class\"":[182],"\"Scarce-Image,\"":[184],"respectively":[185],"corresponding":[186],"shortage":[189],"images.":[194],"Finally,":[195],"analyze":[197],"effect":[199],"applying":[201],"various":[202],"additional":[203],"supervision":[204],"sources":[205],"under":[206],"proposed":[208],"settings.":[209],"Our":[210,229],"experiments":[211],"demonstrate":[212],"that":[213],"densely":[214],"labeling":[215],"indeed":[222],"largely":[223],"remedy":[224],"data":[227],"constraints.":[228],"code":[230],"benchmark":[232],"are":[233],"at":[235],"https://github.com/BinahHu/ADE-FewShot.":[236]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
