{"id":"https://openalex.org/W4386065561","doi":"https://doi.org/10.1109/cvpr52729.2023.01892","title":"ProD: Prompting-to-disentangle Domain Knowledge for Cross-domain Few-shot Image Classification","display_name":"ProD: Prompting-to-disentangle Domain Knowledge for Cross-domain Few-shot Image Classification","publication_year":2023,"publication_date":"2023-06-01","ids":{"openalex":"https://openalex.org/W4386065561","doi":"https://doi.org/10.1109/cvpr52729.2023.01892"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr52729.2023.01892","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52729.2023.01892","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","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/A5069632856","display_name":"Tianyi Ma","orcid":"https://orcid.org/0000-0002-1042-8700"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]},{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU","CN"],"is_corresponding":true,"raw_author_name":"Tianyi Ma","raw_affiliation_strings":["University of Technology Sydney","Baidu Inc"],"affiliations":[{"raw_affiliation_string":"University of Technology Sydney","institution_ids":["https://openalex.org/I114017466"]},{"raw_affiliation_string":"Baidu Inc","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101677993","display_name":"Yifan Sun","orcid":"https://orcid.org/0000-0001-9859-8300"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifan Sun","raw_affiliation_strings":["Baidu Inc"],"affiliations":[{"raw_affiliation_string":"Baidu Inc","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020316185","display_name":"Zongxin Yang","orcid":"https://orcid.org/0000-0001-8783-8313"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zongxin Yang","raw_affiliation_strings":["Zhejiang University"],"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101577828","display_name":"Yi Yang","orcid":"https://orcid.org/0000-0002-6679-4021"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Yang","raw_affiliation_strings":["Zhejiang University"],"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5069632856"],"corresponding_institution_ids":["https://openalex.org/I114017466","https://openalex.org/I98301712"],"apc_list":null,"apc_paid":null,"fwci":5.6411,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.96841977,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"19754","last_page":"19763"},"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":0.9991000294685364,"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":0.9991000294685364,"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/T10515","display_name":"Cancer-related molecular mechanisms research","score":0.9463000297546387,"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"}},{"id":"https://openalex.org/T11581","display_name":"Viral Infections and Outbreaks Research","score":0.9409000277519226,"subfield":{"id":"https://openalex.org/subfields/2725","display_name":"Infectious Diseases"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6852272748947144},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5909228324890137},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5666120648384094},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5645798444747925},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5480839610099792},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5331800580024719},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5174806118011475},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4903126060962677},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4813404977321625},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.47317129373550415},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35191071033477783},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34143900871276855},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23319116234779358},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0782579779624939}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6852272748947144},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5909228324890137},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5666120648384094},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5645798444747925},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5480839610099792},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5331800580024719},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5174806118011475},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4903126060962677},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4813404977321625},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.47317129373550415},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35191071033477783},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34143900871276855},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23319116234779358},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0782579779624939},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr52729.2023.01892","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52729.2023.01892","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W1852255964","https://openalex.org/W1920962657","https://openalex.org/W2096873754","https://openalex.org/W2103490241","https://openalex.org/W2117539524","https://openalex.org/W2138011018","https://openalex.org/W2194775991","https://openalex.org/W2311414730","https://openalex.org/W2395579298","https://openalex.org/W2601450892","https://openalex.org/W2604763608","https://openalex.org/W2732026016","https://openalex.org/W2797977484","https://openalex.org/W2798658180","https://openalex.org/W2806187986","https://openalex.org/W2963341924","https://openalex.org/W2963741406","https://openalex.org/W2964105864","https://openalex.org/W3001411605","https://openalex.org/W3025345330","https://openalex.org/W3035723985","https://openalex.org/W3094502228","https://openalex.org/W3110608229","https://openalex.org/W3118284102","https://openalex.org/W3133542152","https://openalex.org/W3149860822","https://openalex.org/W3179539006","https://openalex.org/W3185341429","https://openalex.org/W3189329097","https://openalex.org/W3189656202","https://openalex.org/W3193300915","https://openalex.org/W3198263118","https://openalex.org/W3198377975","https://openalex.org/W3202165894","https://openalex.org/W3203048322","https://openalex.org/W4288076010","https://openalex.org/W4288287305","https://openalex.org/W4292779060","https://openalex.org/W4297813345","https://openalex.org/W4312235843","https://openalex.org/W4312473311","https://openalex.org/W6639968131","https://openalex.org/W6674764686","https://openalex.org/W6717697761","https://openalex.org/W6735236233","https://openalex.org/W6736057607","https://openalex.org/W6752160200","https://openalex.org/W6758126075","https://openalex.org/W6780018965","https://openalex.org/W6801756507","https://openalex.org/W6810601475"],"related_works":["https://openalex.org/W4287776258","https://openalex.org/W2811390910","https://openalex.org/W2146076056","https://openalex.org/W4312376745","https://openalex.org/W2913302899","https://openalex.org/W3027997911","https://openalex.org/W2767651786","https://openalex.org/W2144059113","https://openalex.org/W3003836766","https://openalex.org/W2546942002"],"abstract_inverted_index":{"This":[0],"paper":[1],"considers":[2],"few-shot":[3,222],"image":[4],"classification":[5,16],"under":[6],"the":[7,11,20,34,39,46,61,68,72,76,84,97,116,120,126,129,134,144,148,163,170,184,189,195,201,211,230,244],"cross-domain":[8,176,221],"scenario,":[9],"where":[10],"train-to-test":[12],"domain":[13,21,208],"gap":[14],"compromises":[15],"accuracy.":[17],"To":[18],"mitigate":[19],"gap,":[22],"we":[23],"propose":[24],"a":[25,30,50,90,93,104,132,157,240],"prompting-to-disentangle":[26],"(ProD)":[27],"method":[28],"through":[29,210],"novel":[31,171],"exploration":[32],"with":[33,49,143],"prompting":[35,69,212],"mechanism.":[36,213],"ProD":[37,65,88,218,228],"adopts":[38],"popular":[40],"multi-domain":[41],"training":[42,117,164,190],"scheme":[43],"and":[44,79,92,100,112,138,204],"extracts":[45],"backbone":[47,85,98],"feature":[48,99],"standard":[51],"Convolutional":[52],"Neural":[53],"Network.":[54],"Based":[55],"on":[56,128,226],"these":[57],"two":[58,145],"common":[59],"practices,":[60],"key":[62],"point":[63],"of":[64,243],"is":[66,110,123,198],"using":[67],"mechanism":[70],"in":[71,141],"transformer":[73,135],"to":[74,96,237],"disentangle":[75],"domain-general":[77],"(DG)":[78],"domain-specific":[80],"(DS)":[81],"knowledge":[82,209],"from":[83,125,200,234],"feature.":[86],"Specifically,":[87],"concatenates":[89],"DG":[91,108,137,159,185],"DS":[94,121,139,196],"prompt":[95,109,122,160,186,197],"feeds":[101],"them":[102],"into":[103],"lightweight":[105],"transformer.":[106],"The":[107,175],"learnable":[111],"shared":[113],"by":[114,182],"all":[115,162,215],"domains,":[118],"while":[119],"generated":[124,199],"domain-of-interest":[127],"fly.":[130],"As":[131],"result,":[133],"outputs":[136],"features":[140],"parallel":[142],"prompts,":[146],"yielding":[147],"disentangling":[149],"effect.":[150],"We":[151],"show":[152],"that:":[153],"1)":[154],"Simply":[155],"sharing":[156],"single":[158],"for":[161],"domains":[165],"already":[166],"improves":[167,220,229],"generalization":[168,177],"towards":[169,188],"test":[172,207],"domain.":[173],"2)":[174],"can":[178,205],"be":[179],"further":[180],"reinforced":[181],"making":[183],"neutral":[187],"domains.":[191],"3)":[192],"When":[193],"inference,":[194],"support":[202],"samples":[203],"capture":[206],"Combining":[214],"three":[216],"benefits,":[217],"significantly":[219],"classification.":[223],"For":[224],"instance,":[225],"CUB,":[227],"5-way":[231],"5-shot":[232],"ac-curacy":[233],"73.56%":[235],"(baseline)":[236],"79.19%,":[238],"setting":[239],"new":[241],"state":[242],"art.":[245]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":18},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-17T09:09:15.849793","created_date":"2025-10-10T00:00:00"}
