{"id":"https://openalex.org/W4390190838","doi":"https://doi.org/10.1109/iccvw60793.2023.00104","title":"SelectNAdapt: Support Set Selection for Few-Shot Domain Adaptation","display_name":"SelectNAdapt: Support Set Selection for Few-Shot Domain Adaptation","publication_year":2023,"publication_date":"2023-10-02","ids":{"openalex":"https://openalex.org/W4390190838","doi":"https://doi.org/10.1109/iccvw60793.2023.00104"},"language":"en","primary_location":{"id":"doi:10.1109/iccvw60793.2023.00104","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccvw60793.2023.00104","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)","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/A5082646779","display_name":"Youssef Dawoud","orcid":null},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Youssef Dawoud","raw_affiliation_strings":["Friedrich-Alexander-Universität Erlangen-Nürnberg,Erlangen,Germany"],"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander-Universität Erlangen-Nürnberg,Erlangen,Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029215323","display_name":"Gustavo Carneiro","orcid":"https://orcid.org/0000-0002-5571-6220"},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Gustavo Carneiro","raw_affiliation_strings":["University of Surrey,United Kingdom","University of Surrey, United Kingdom"],"affiliations":[{"raw_affiliation_string":"University of Surrey,United Kingdom","institution_ids":["https://openalex.org/I28290843"]},{"raw_affiliation_string":"University of Surrey, United Kingdom","institution_ids":["https://openalex.org/I28290843"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027065196","display_name":"Vasileios Belagiannis","orcid":"https://orcid.org/0000-0003-0960-8453"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Vasileios Belagiannis","raw_affiliation_strings":["Friedrich-Alexander-Universität Erlangen-Nürnberg,Erlangen,Germany"],"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander-Universität Erlangen-Nürnberg,Erlangen,Germany","institution_ids":["https://openalex.org/I181369854"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5082646779"],"corresponding_institution_ids":["https://openalex.org/I181369854"],"apc_list":null,"apc_paid":null,"fwci":1.049,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.82063148,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"973","last_page":"982"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9836000204086304,"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":0.9409000277519226,"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":0.785093367099762},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7393957376480103},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6857963800430298},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.6622074842453003},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6558851003646851},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5963351130485535},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.541386604309082},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5206609964370728},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5115090608596802},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.4522068202495575},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4483253061771393},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42701655626296997},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.41555488109588623},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41268616914749146},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.15070632100105286},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08213454484939575}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.785093367099762},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7393957376480103},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6857963800430298},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.6622074842453003},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6558851003646851},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5963351130485535},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.541386604309082},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5206609964370728},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5115090608596802},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.4522068202495575},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4483253061771393},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42701655626296997},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.41555488109588623},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41268616914749146},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.15070632100105286},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08213454484939575},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccvw60793.2023.00104","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccvw60793.2023.00104","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1722318740","https://openalex.org/W1821462560","https://openalex.org/W1995875735","https://openalex.org/W2101234009","https://openalex.org/W2117155597","https://openalex.org/W2211456655","https://openalex.org/W2299668505","https://openalex.org/W2749988060","https://openalex.org/W2762534372","https://openalex.org/W2763549966","https://openalex.org/W2766897166","https://openalex.org/W2785325870","https://openalex.org/W2786462443","https://openalex.org/W2789758093","https://openalex.org/W2910745941","https://openalex.org/W2958360136","https://openalex.org/W2962687275","https://openalex.org/W2962937599","https://openalex.org/W2963532621","https://openalex.org/W2963993484","https://openalex.org/W2964059111","https://openalex.org/W2970119729","https://openalex.org/W2982376094","https://openalex.org/W3009033475","https://openalex.org/W3011304563","https://openalex.org/W3034562924","https://openalex.org/W3036224891","https://openalex.org/W3036825277","https://openalex.org/W3119543788","https://openalex.org/W3125348404","https://openalex.org/W3130794141","https://openalex.org/W3201074629","https://openalex.org/W4212863985","https://openalex.org/W4214715922","https://openalex.org/W4285603595","https://openalex.org/W4289639938","https://openalex.org/W4312365002","https://openalex.org/W4312897837","https://openalex.org/W4319301008","https://openalex.org/W6631190155","https://openalex.org/W6638523607","https://openalex.org/W6639480849","https://openalex.org/W6677530066","https://openalex.org/W6697673422","https://openalex.org/W6713955831","https://openalex.org/W6726497184","https://openalex.org/W6743289643","https://openalex.org/W6747899497","https://openalex.org/W6758130285","https://openalex.org/W6767680423","https://openalex.org/W6774187218","https://openalex.org/W6774314701","https://openalex.org/W6779923881","https://openalex.org/W6779997284","https://openalex.org/W6780128236","https://openalex.org/W6780233385","https://openalex.org/W6788125050","https://openalex.org/W6795508594","https://openalex.org/W6800892926"],"related_works":["https://openalex.org/W2997567050","https://openalex.org/W4298130764","https://openalex.org/W2804364458","https://openalex.org/W2132641928","https://openalex.org/W4310225030","https://openalex.org/W2090259340","https://openalex.org/W1483272040","https://openalex.org/W4394775207","https://openalex.org/W4283211831","https://openalex.org/W2798287483"],"abstract_inverted_index":{"Generalisation":[0],"of":[1,86,115,127],"deep":[2,28],"neural":[3,29],"networks":[4,30],"becomes":[5],"vulnerable":[6],"when":[7],"distribution":[8],"shifts":[9],"are":[10,92],"encountered":[11],"between":[12],"train":[13],"(source)":[14],"and":[15,44,95,133,183],"test":[16],"(target)":[17],"domain":[18,21,35,39,89,118,131,163,173],"data.":[19,119],"Few-shot":[20],"adaptation":[22,106,174],"mitigates":[23],"this":[24],"issue":[25],"by":[26,154],"adapting":[27,67],"pre-trained":[31,69],"on":[32,156,170],"the":[33,37,49,58,68,73,84,87,98,104,116,128,184],"source":[34,70],"to":[36,72,82,112,180],"target":[38,50,74,88,117,130,137,162],"using":[40,139],"a":[41,123,140,151],"randomly":[42,56],"selected":[43],"annotated":[45,94],"support":[46,59,99],"set":[47,60],"from":[48],"domain.":[51,75],"This":[52],"paper":[53],"argues":[54],"that":[55],"selecting":[57],"can":[61],"be":[62],"further":[63],"improved":[64],"for":[65,103,158,176],"effectively":[66],"models":[71],"Alternatively,":[76],"we":[77,108,121,145],"propose":[78,122],"SelectNAdapt,":[79],"an":[80],"algorithm":[81],"curate":[83],"selection":[85,148],"samples,":[90],"which":[91],"then":[93],"included":[96],"in":[97],"set.":[100],"In":[101],"particular,":[102],"K-shot":[105],"problem,":[107],"first":[109],"leverage":[110],"self-supervision":[111],"learn":[113],"features":[114,132],"Then,":[120],"per-class":[124],"clustering":[125,159],"scheme":[126],"learned":[129],"select":[134],"K":[135],"representative":[136],"samples":[138],"distance-based":[141],"scoring":[142],"function.":[143],"Finally,":[144],"bring":[146],"our":[147],"setup":[149],"towards":[150],"practical":[152],"ground":[153],"relying":[155],"pseudo-labels":[157],"semantically":[160],"similar":[161],"samples.":[164],"Our":[165],"experiments":[166],"show":[167],"promising":[168],"results":[169],"three":[171],"few-shot":[172],"benchmarks":[175],"image":[177],"recognition":[178],"compared":[179],"related":[181],"approaches":[182],"standard":[185],"random":[186],"selection.":[187]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}