{"id":"https://openalex.org/W3041350610","doi":"https://doi.org/10.1145/3391624","title":"Few-shot Food Recognition via Multi-view Representation Learning","display_name":"Few-shot Food Recognition via Multi-view Representation Learning","publication_year":2020,"publication_date":"2020-07-07","ids":{"openalex":"https://openalex.org/W3041350610","doi":"https://doi.org/10.1145/3391624","mag":"3041350610"},"language":"en","primary_location":{"id":"doi:10.1145/3391624","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3391624","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Multimedia Computing, Communications, and Applications","raw_type":"journal-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/A5085719285","display_name":"Shuqiang Jiang","orcid":"https://orcid.org/0000-0002-1596-4326"},"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/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuqiang Jiang","raw_affiliation_strings":["Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-1596-4326","affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039322394","display_name":"Weiqing Min","orcid":"https://orcid.org/0000-0001-6668-9208"},"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/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiqing Min","raw_affiliation_strings":["Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071514960","display_name":"Yongqiang Lyu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yongqiang Lyu","raw_affiliation_strings":["Qingdao KingAgroot Precision Agriculture Technology Co., Ltd, Qingdao, Shandong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Qingdao KingAgroot Precision Agriculture Technology Co., Ltd, Qingdao, Shandong, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023302316","display_name":"Linhu Liu","orcid":"https://orcid.org/0000-0001-5253-6649"},"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/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linhu Liu","raw_affiliation_strings":["Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.0619,"has_fulltext":false,"cited_by_count":46,"citation_normalized_percentile":{"value":0.86439367,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"16","issue":"3","first_page":"1","last_page":"20"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10866","display_name":"Nutritional Studies and Diet","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/2739","display_name":"Public Health, Environmental and Occupational Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10836","display_name":"Metabolomics and Mass Spectrometry Studies","score":0.9704999923706055,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7062705755233765},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6698083281517029},{"id":"https://openalex.org/keywords/ingredient","display_name":"Ingredient","score":0.5895702838897705},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5386471748352051},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46808773279190063},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4620574712753296},{"id":"https://openalex.org/keywords/disjoint-sets","display_name":"Disjoint sets","score":0.4550434648990631},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.44018369913101196},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4319208860397339},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14255014061927795}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7062705755233765},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6698083281517029},{"id":"https://openalex.org/C2780589914","wikidata":"https://www.wikidata.org/wiki/Q10675206","display_name":"Ingredient","level":2,"score":0.5895702838897705},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5386471748352051},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46808773279190063},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4620574712753296},{"id":"https://openalex.org/C45340560","wikidata":"https://www.wikidata.org/wiki/Q215382","display_name":"Disjoint sets","level":2,"score":0.4550434648990631},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.44018369913101196},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4319208860397339},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14255014061927795},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C31903555","wikidata":"https://www.wikidata.org/wiki/Q1637030","display_name":"Food science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3391624","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3391624","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Multimedia Computing, Communications, and Applications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5400000214576721,"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2"}],"awards":[{"id":"https://openalex.org/G4531242726","display_name":null,"funder_award_id":"61532018, 61972378, and U19B2040","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"},{"id":"https://openalex.org/F4320336648","display_name":"National Program for Support of Top-notch Young Professionals","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":69,"referenced_works":["https://openalex.org/W12634471","https://openalex.org/W56385144","https://openalex.org/W1496513042","https://openalex.org/W1518729828","https://openalex.org/W1686810756","https://openalex.org/W1849277567","https://openalex.org/W1978132383","https://openalex.org/W1982635469","https://openalex.org/W2000105909","https://openalex.org/W2055527244","https://openalex.org/W2085625911","https://openalex.org/W2094931013","https://openalex.org/W2100124084","https://openalex.org/W2114168642","https://openalex.org/W2115733720","https://openalex.org/W2125269571","https://openalex.org/W2126204609","https://openalex.org/W2163969215","https://openalex.org/W2194775991","https://openalex.org/W2206370378","https://openalex.org/W2236282269","https://openalex.org/W2342662179","https://openalex.org/W2358876993","https://openalex.org/W2399033357","https://openalex.org/W2401823607","https://openalex.org/W2512351403","https://openalex.org/W2526198870","https://openalex.org/W2529459268","https://openalex.org/W2531666942","https://openalex.org/W2535808783","https://openalex.org/W2562417371","https://openalex.org/W2563053307","https://openalex.org/W2583892095","https://openalex.org/W2587892873","https://openalex.org/W2594908799","https://openalex.org/W2601450892","https://openalex.org/W2604763608","https://openalex.org/W2613010453","https://openalex.org/W2614641536","https://openalex.org/W2623012778","https://openalex.org/W2625674597","https://openalex.org/W2724616073","https://openalex.org/W2737041163","https://openalex.org/W2737725206","https://openalex.org/W2740068783","https://openalex.org/W2740463150","https://openalex.org/W2742792558","https://openalex.org/W2761189739","https://openalex.org/W2798836702","https://openalex.org/W2890018557","https://openalex.org/W2895671740","https://openalex.org/W2914393402","https://openalex.org/W2921891839","https://openalex.org/W2945774199","https://openalex.org/W2960416371","https://openalex.org/W2962810352","https://openalex.org/W2962858109","https://openalex.org/W2963341924","https://openalex.org/W2963446712","https://openalex.org/W2963680240","https://openalex.org/W2964105864","https://openalex.org/W2966316879","https://openalex.org/W2972610293","https://openalex.org/W2981631843","https://openalex.org/W2981771452","https://openalex.org/W2990138404","https://openalex.org/W3104226648","https://openalex.org/W4236965008","https://openalex.org/W7055713322"],"related_works":["https://openalex.org/W2490316842","https://openalex.org/W1650653924","https://openalex.org/W4221018629","https://openalex.org/W2088663511","https://openalex.org/W1997883897","https://openalex.org/W2905271011","https://openalex.org/W3164948662","https://openalex.org/W4289536128","https://openalex.org/W3153597579","https://openalex.org/W1872833176"],"abstract_inverted_index":{"This":[0],"article":[1],"considers":[2],"the":[3,117,207,252],"problem":[4],"of":[5,34,86,129,137,169,191,209,221,254],"few-shot":[6,64,110,234,255],"learning":[7,193],"for":[8,63,185,233],"food":[9,12,22,29,41,65,106,111,202,235,256],"recognition.":[10,66,107,236,257],"Automatic":[11],"recognition":[13,30],"can":[14,115,250],"support":[15],"various":[16],"applications,":[17],"e.g.,":[18],"dietary":[19],"assessment":[20],"and":[21,37,83,92,97,123,150,195,226],"journaling.":[23],"Most":[24],"existing":[25],"works":[26],"focus":[27],"on":[28,188,200],"with":[31,43],"large":[32],"numbers":[33],"labelled":[35],"samples,":[36],"fail":[38],"to":[39,58,77,94,173],"recognize":[40],"categories":[42,122],"few":[44],"samples.":[45],"To":[46,126],"address":[47],"this":[48],"problem,":[49],"we":[50,72,132,216],"propose":[51],"a":[52,162],"Multi-View":[53],"Few-Shot":[54],"Learning":[55],"(MVFSL)":[56],"framework":[57],"explore":[59],"additional":[60],"ingredient":[61,113,130,231,244],"information":[62,114,232,245],"Besides":[67],"category-oriented":[68,95],"deep":[69,75,148],"visual":[70],"features,":[71,96],"introduce":[73],"ingredient-supervised":[74],"network":[76],"extract":[78],"ingredient-oriented":[79,88],"features.":[80],"As":[81],"general":[82],"intermediate":[84],"attributes":[85],"food,":[87],"features":[89,138],"are":[90],"informative":[91],"complementary":[93],"thus":[98],"they":[99],"play":[100],"an":[101,182],"important":[102],"role":[103],"in":[104,109,181,211],"improving":[105],"Particularly":[108],"recognition,":[112],"bridge":[116],"gap":[118],"between":[119],"disjoint":[120],"training":[121],"test":[124],"categories.":[125],"take":[127],"advantage":[128,208],"information,":[131],"fuse":[133],"these":[134,247],"two":[135,189,219,248],"kinds":[136],"by":[139,229],"first":[140],"combining":[141],"their":[142,146],"feature":[143,154,176,192,213],"maps":[144],"from":[145],"respective":[147],"networks":[149,249],"then":[151],"convolving":[152],"combined":[153],"maps.":[155],"Such":[156],"convolution":[157],"is":[158,167,179],"further":[159],"incorporated":[160],"into":[161,246],"multi-view":[163,212],"relation":[164,196],"network,":[165],"which":[166],"capable":[168],"comparing":[170],"pairwise":[171],"images":[172],"enable":[174],"fine-grained":[175],"learning.":[177],"MVFSL":[178,210],"trained":[180],"end-to-end":[183],"fashion":[184],"joint":[186],"optimization":[187],"types":[190,220],"subnetworks":[194],"subnetworks.":[197],"Extensive":[198],"experiments":[199],"different":[201],"datasets":[203],"have":[204,239],"consistently":[205],"demonstrated":[206],"fusion.":[214],"Furthermore,":[215],"extend":[217],"another":[218],"networks,":[222],"namely,":[223],"Siamese":[224],"Network":[225],"Matching":[227],"Network,":[228],"introducing":[230,243],"Experimental":[237],"results":[238],"also":[240],"shown":[241],"that":[242],"improve":[251],"performance":[253]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":3}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
