{"id":"https://openalex.org/W2905169750","doi":"https://doi.org/10.1609/aaai.v33i01.33018489","title":"Few-Shot Image and Sentence Matching via Gated Visual-Semantic Embedding","display_name":"Few-Shot Image and Sentence Matching via Gated Visual-Semantic Embedding","publication_year":2019,"publication_date":"2019-07-17","ids":{"openalex":"https://openalex.org/W2905169750","doi":"https://doi.org/10.1609/aaai.v33i01.33018489","mag":"2905169750"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v33i01.33018489","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33018489","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4866/4739","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4866/4739","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101550628","display_name":"Yan Huang","orcid":"https://orcid.org/0000-0002-8239-7229"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Huang","raw_affiliation_strings":["Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011037821","display_name":"Yang Long","orcid":"https://orcid.org/0000-0002-2445-6112"},"institutions":[{"id":"https://openalex.org/I84884186","display_name":"Newcastle University","ror":"https://ror.org/01kj2bm70","country_code":"GB","type":"education","lineage":["https://openalex.org/I84884186"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yang Long","raw_affiliation_strings":["Newcastle University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Newcastle University","institution_ids":["https://openalex.org/I84884186"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5115602506","display_name":"Liang Wang","orcid":"https://orcid.org/0000-0001-5224-8647"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang Wang","raw_affiliation_strings":["National Laboratory of Pattern Recognition"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern Recognition","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.647,"has_fulltext":true,"cited_by_count":29,"citation_normalized_percentile":{"value":0.89802286,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"33","issue":"01","first_page":"8489","last_page":"8496"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9994999766349792,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9994999766349792,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9883000254631042,"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":0.9855999946594238,"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/computer-science","display_name":"Computer science","score":0.7716489434242249},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6952167749404907},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6838817000389099},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6365839242935181},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6047174334526062},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5863417387008667},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5250796675682068},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5227860808372498},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5028919577598572},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4680134057998657},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4513888657093048},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3994784951210022},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10422694683074951}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7716489434242249},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6952167749404907},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6838817000389099},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6365839242935181},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6047174334526062},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5863417387008667},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5250796675682068},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5227860808372498},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5028919577598572},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4680134057998657},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4513888657093048},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3994784951210022},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10422694683074951},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1609/aaai.v33i01.33018489","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33018489","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4866/4739","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:durham-repository.worktribe.com:1142112","is_oa":true,"landing_page_url":"https://durham-repository.worktribe.com/output/1142112","pdf_url":null,"source":{"id":"https://openalex.org/S4306400188","display_name":"Durham Research Online (Durham University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I190082696","host_organization_name":"Durham University","host_organization_lineage":["https://openalex.org/I190082696"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Presentation / Conference Contribution"},{"id":"pmh:oai:ojs.aaai.org:article/4866","is_oa":false,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/4866","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2159-5399","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v33i01.33018489","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33018489","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4866/4739","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7300000190734863}],"awards":[{"id":"https://openalex.org/G1546592745","display_name":null,"funder_award_id":"4162058","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1619977957","display_name":"Intelligent Healthcare Systems for Large-scale Populations","funder_award_id":"MR/S003916/1","funder_id":"https://openalex.org/F4320334626","funder_display_name":"Medical Research Council"},{"id":"https://openalex.org/G3000430873","display_name":null,"funder_award_id":"MR/S003916/1","funder_id":"https://openalex.org/F4320334626","funder_display_name":"Medical Research Council"},{"id":"https://openalex.org/G4952514591","display_name":null,"funder_award_id":"2016YFB1001000","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G5174227071","display_name":null,"funder_award_id":"61633021","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G5858177368","display_name":null,"funder_award_id":"61525306","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6018366371","display_name":null,"funder_award_id":"61721004","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G6132059711","display_name":null,"funder_award_id":"61420106015","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6431871145","display_name":null,"funder_award_id":"61721004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7010190359","display_name":"\u6df1\u5ea6\u8ba4\u77e5\u795e\u7ecf\u7f51\u7edc\u7406\u8bba\u4e0e\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61633021","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7685726040","display_name":null,"funder_award_id":"MR/S003916/1","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8247184986","display_name":null,"funder_award_id":"61525306","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8842693076","display_name":null,"funder_award_id":"2016YFB1001000","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/F4320334626","display_name":"Medical Research Council","ror":"https://ror.org/03x94j517"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2905169750.pdf","grobid_xml":"https://content.openalex.org/works/W2905169750.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W1514535095","https://openalex.org/W1527575280","https://openalex.org/W1686810756","https://openalex.org/W1905882502","https://openalex.org/W1916445035","https://openalex.org/W2173180041","https://openalex.org/W2185175083","https://openalex.org/W2284126738","https://openalex.org/W2287889828","https://openalex.org/W2346425926","https://openalex.org/W2527238922","https://openalex.org/W2546696630","https://openalex.org/W2552579943","https://openalex.org/W2613718673","https://openalex.org/W2772385709","https://openalex.org/W2778100917","https://openalex.org/W2788967361","https://openalex.org/W2790040974","https://openalex.org/W6629028937","https://openalex.org/W6639102338","https://openalex.org/W6678360021","https://openalex.org/W6685183736","https://openalex.org/W6687483927","https://openalex.org/W6724699187","https://openalex.org/W6750666490"],"related_works":["https://openalex.org/W2729514902","https://openalex.org/W2024160000","https://openalex.org/W2773500201","https://openalex.org/W2061273563","https://openalex.org/W2285052147","https://openalex.org/W4287995534","https://openalex.org/W2743258233","https://openalex.org/W2998168123","https://openalex.org/W1972656095","https://openalex.org/W2970216048"],"abstract_inverted_index":{"Although":[0],"image":[1,36,174],"and":[2,37,40,66,85,89,91,113,120,172,175,178],"sentence":[3,38,176],"matching":[4],"has":[5,17],"been":[6],"widely":[7],"studied,":[8],"its":[9],"intrinsic":[10],"few-shot":[11,35,171],"problem":[12,33],"is":[13],"commonly":[14],"ignored,":[15],"which":[16],"become":[18],"a":[19,42],"bottleneck":[20],"for":[21,81,104],"further":[22],"performance":[23],"improvement.":[24],"In":[25],"this":[26,31],"work,":[27],"we":[28,164],"focus":[29],"on":[30,160,191],"challenging":[32],"of":[34,55,61,118,170,182],"matching,":[39,177],"propose":[41],"Gated":[43],"Visual-Semantic":[44],"Embedding":[45],"(GVSE)":[46],"model":[47,53,109,185],"to":[48,77,100],"deal":[49],"with":[50,142],"it.":[51],"The":[52,70],"consists":[54],"three":[56],"corporative":[57],"modules":[58,141],"in":[59,87,115,168],"terms":[60,169],"uncommon":[62,71,83],"VSE,":[63,65],"common":[64,111,123],"gated":[67,146],"metric":[68,147],"fusion.":[69],"VSE":[72,124,140],"exploits":[73],"external":[74],"auxiliary":[75],"resources":[76],"extract":[78],"generic":[79],"features":[80],"representing":[82],"instances":[84,112],"words":[86,114],"images":[88,119],"sentences,":[90,121],"then":[92],"integrates":[93],"them":[94,152],"by":[95,153,186],"modeling":[96],"their":[97,126,156],"semantic":[98],"relation":[99],"obtain":[101],"global":[102],"representations":[103,128],"association":[105],"analysis.":[106],"To":[107],"better":[108],"other":[110],"rest":[116],"content":[117],"the":[122,138,145,161,180,183,188],"learns":[125],"discriminative":[127],"directly":[129],"from":[130,137],"scratch.":[131],"After":[132],"obtaining":[133],"two":[134,139,192],"similarity":[135],"metrics":[136],"different":[143],"advantages,":[144],"fusion":[148],"module":[149],"adaptively":[150],"fuses":[151],"automatically":[154],"balancing":[155],"relative":[157],"importance.":[158],"Based":[159],"fused":[162],"metric,":[163],"perform":[165],"extensive":[166],"experiments":[167],"conventional":[173],"demonstrate":[179],"effectiveness":[181],"proposed":[184],"achieving":[187],"state-of-the-art":[189],"results":[190],"public":[193],"benchmark":[194],"datasets.":[195]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}