{"id":"https://openalex.org/W4304084239","doi":"https://doi.org/10.1145/3503161.3548052","title":"TGDM: Target Guided Dynamic Mixup for Cross-Domain Few-Shot Learning","display_name":"TGDM: Target Guided Dynamic Mixup for Cross-Domain Few-Shot Learning","publication_year":2022,"publication_date":"2022-10-10","ids":{"openalex":"https://openalex.org/W4304084239","doi":"https://doi.org/10.1145/3503161.3548052"},"language":"en","primary_location":{"id":"doi:10.1145/3503161.3548052","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503161.3548052","pdf_url":null,"source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2210.05392","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016169949","display_name":"Linhai Zhuo","orcid":"https://orcid.org/0000-0002-5557-2896"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Linhai Zhuo","raw_affiliation_strings":["Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072248915","display_name":"Yuqian Fu","orcid":"https://orcid.org/0000-0002-0412-5500"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuqian Fu","raw_affiliation_strings":["Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100373492","display_name":"Jingjing Chen","orcid":"https://orcid.org/0000-0003-3148-264X"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingjing Chen","raw_affiliation_strings":["Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101488072","display_name":"Yixin Cao","orcid":"https://orcid.org/0000-0002-1632-7812"},"institutions":[{"id":"https://openalex.org/I79891267","display_name":"Singapore Management University","ror":"https://ror.org/050qmg959","country_code":"SG","type":"education","lineage":["https://openalex.org/I79891267"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yixin Cao","raw_affiliation_strings":["Singapore Management University, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"Singapore Management University, Singapore, Singapore","institution_ids":["https://openalex.org/I79891267"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047962986","display_name":"Yu\u2013Gang Jiang","orcid":"https://orcid.org/0000-0002-1907-8567"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu-Gang Jiang","raw_affiliation_strings":["Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5016169949"],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":2.1919,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.897864,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"6368","last_page":"6376"},"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":0.9998000264167786,"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":0.9998000264167786,"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":0.9751999974250793,"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/T10515","display_name":"Cancer-related molecular mechanisms research","score":0.963100016117096,"subfield":{"id":"https://openalex.org/subfields/1306","display_name":"Cancer Research"},"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/computer-science","display_name":"Computer science","score":0.7992908954620361},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7153574228286743},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.7007302045822144},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5874647498130798},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5351783633232117},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.51563560962677},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5035249590873718},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.4164234697818756},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.353003591299057},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3339029550552368},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08394807577133179}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7992908954620361},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7153574228286743},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.7007302045822144},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5874647498130798},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5351783633232117},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.51563560962677},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5035249590873718},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.4164234697818756},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.353003591299057},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3339029550552368},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08394807577133179},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3503161.3548052","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503161.3548052","pdf_url":null,"source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Multimedia","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2210.05392","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2210.05392","pdf_url":"https://arxiv.org/pdf/2210.05392","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":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":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:ink.library.smu.edu.sg:sis_research-8456","is_oa":true,"landing_page_url":"https://ink.library.smu.edu.sg/sis_research/7453","pdf_url":null,"source":{"id":"https://openalex.org/S4377196871","display_name":"Institutional Knowledge (InK) - Institutional Knowledge at Singapore Management University (Singapore Management University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79891267","host_organization_name":"Singapore Management University","host_organization_lineage":["https://openalex.org/I79891267"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://doi.org/10.1145/3503161.3548052","raw_type":"Conference Proceeding Article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2210.05392","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2210.05392","pdf_url":"https://arxiv.org/pdf/2210.05392","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":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":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1797268635","https://openalex.org/W2138011018","https://openalex.org/W2194775991","https://openalex.org/W2601450892","https://openalex.org/W2604763608","https://openalex.org/W2732026016","https://openalex.org/W2753160622","https://openalex.org/W2765407302","https://openalex.org/W2787501667","https://openalex.org/W2795282075","https://openalex.org/W2797977484","https://openalex.org/W2891021639","https://openalex.org/W2904008038","https://openalex.org/W2947380870","https://openalex.org/W2952322298","https://openalex.org/W2963341924","https://openalex.org/W2964105864","https://openalex.org/W2964112702","https://openalex.org/W2981874246","https://openalex.org/W2992308087","https://openalex.org/W2994088087","https://openalex.org/W3001411605","https://openalex.org/W3014776867","https://openalex.org/W3035370595","https://openalex.org/W3035374961","https://openalex.org/W3086731747","https://openalex.org/W3092900959","https://openalex.org/W3093455342","https://openalex.org/W3110608229","https://openalex.org/W3123120463","https://openalex.org/W3135228776","https://openalex.org/W3139079945","https://openalex.org/W3140588259","https://openalex.org/W3159907343","https://openalex.org/W3184083006","https://openalex.org/W3189329097","https://openalex.org/W3189656202","https://openalex.org/W3198519958","https://openalex.org/W3199510075","https://openalex.org/W3203015511","https://openalex.org/W3207342895","https://openalex.org/W3211980987","https://openalex.org/W3217059328","https://openalex.org/W4226409656","https://openalex.org/W4285295719","https://openalex.org/W4287639816","https://openalex.org/W4288073030","https://openalex.org/W4293412117","https://openalex.org/W4300833946","https://openalex.org/W4319235387"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W2745001401","https://openalex.org/W4321353415","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W972276598","https://openalex.org/W3144173820","https://openalex.org/W4318813552","https://openalex.org/W2576964996"],"abstract_inverted_index":{"Given":[0],"sufficient":[1],"training":[2],"data":[3,100],"on":[4,24,46,181,205,211],"the":[5,25,36,47,51,69,72,78,98,103,131,138,140,154,164,168,179,186,216],"source":[6,48,70,155],"domain,":[7,156,158,167],"cross-domain":[8],"few-shot":[9],"learning":[10,120,130],"(CD-FSL)":[11],"aims":[12],"at":[13],"recognizing":[14],"new":[15],"classes":[16,152],"with":[17,147],"a":[18,43,88,116,123],"small":[19],"number":[20],"of":[21,42,105,218],"labeled":[22],"examples":[23],"target":[26,52,73,84,90,99,157,183,206],"domain.":[27,53,74,161],"The":[28,111],"key":[29],"to":[30,34,50,76,101,171,178,201],"addressing":[31],"CD-FSL":[32],"is":[33,190],"narrow":[35],"domain":[37,49,63,81],"gap":[38],"and":[39,71,122,159],"transferring":[40],"knowledge":[41,56],"network":[44,118,127,143],"trained":[45,191],"To":[54,135,162],"help":[55],"transfer,":[57],"this":[58],"paper":[59],"introduces":[60],"an":[61,173],"intermediate":[62,80,160,166],"generated":[64],"by":[65],"mixing":[66],"images":[67,107],"in":[68,153],"Specifically,":[75],"generate":[77,163,172],"optimal":[79,132,165,174,203],"for":[82,119,129,150],"different":[83],"data,":[85],"we":[86],"propose":[87],"novel":[89],"guided":[91],"dynamic":[92,109,124],"mixup":[93],"(TGDM)":[94],"framework":[95,114,189],"that":[96,196],"leverages":[97],"guide":[102],"generation":[104,126],"mixed":[106],"via":[108,192],"mixup.":[110],"proposed":[112,141],"TGDM":[113,188,197],"contains":[115,144],"Mixup-3T":[117,142],"classifiers":[121],"ratio":[125,176],"(DRGN)":[128],"mix":[133,175],"ratio.":[134],"better":[136],"transfer":[137],"knowledge,":[139],"three":[145],"branches":[146],"shared":[148],"parameters":[149],"classifying":[151],"DRGN":[169],"learns":[170],"according":[177],"performance":[180,204],"auxiliary":[182],"data.":[184,207],"Then,":[185],"whole":[187],"bi-level":[193],"meta-learning":[194],"so":[195],"can":[198],"rectify":[199],"itself":[200],"achieve":[202],"Extensive":[208],"experimental":[209],"results":[210],"several":[212],"benchmark":[213],"datasets":[214],"verify":[215],"effectiveness":[217],"our":[219],"method.":[220]},"counts_by_year":[{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":3}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}