{"id":"https://openalex.org/W4400975048","doi":"https://doi.org/10.1109/lsp.2024.3433546","title":"Boosting Deepfake Feature Extractors Using Unsupervised Domain Adaptation","display_name":"Boosting Deepfake Feature Extractors Using Unsupervised Domain Adaptation","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4400975048","doi":"https://doi.org/10.1109/lsp.2024.3433546"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2024.3433546","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2024.3433546","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","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":null,"display_name":"Jicheng Li","orcid":"https://orcid.org/0000-0003-4735-6138"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jicheng Li","raw_affiliation_strings":["School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-4735-6138","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102772000","display_name":"Yongjian Hu","orcid":"https://orcid.org/0000-0002-7775-3786"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongjian Hu","raw_affiliation_strings":["School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-7775-3786","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031732848","display_name":"Beibei Liu","orcid":"https://orcid.org/0000-0002-3907-773X"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Beibei Liu","raw_affiliation_strings":["School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-3907-773X","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111268405","display_name":"Zhaolong Gong","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaolong Gong","raw_affiliation_strings":["School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077333494","display_name":"Xiangui Kang","orcid":"https://orcid.org/0000-0002-3134-0353"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangui Kang","raw_affiliation_strings":["Guangdong Key Laboratory of Information Security, and the School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-3134-0353","affiliations":[{"raw_affiliation_string":"Guangdong Key Laboratory of Information Security, and the School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0219,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.76717909,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"31","issue":null,"first_page":"2010","last_page":"2014"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9933000206947327,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9933000206947327,"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":0.9781000018119812,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9746000170707703,"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/boosting","display_name":"Boosting (machine learning)","score":0.7178596258163452},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7032603621482849},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6496483087539673},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.6185608506202698},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5276949405670166},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5190211534500122},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47049570083618164},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.41399461030960083},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24064666032791138},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.12037074565887451}],"concepts":[{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.7178596258163452},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7032603621482849},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6496483087539673},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.6185608506202698},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5276949405670166},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5190211534500122},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47049570083618164},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.41399461030960083},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24064666032791138},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.12037074565887451},{"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},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2024.3433546","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2024.3433546","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W2115252128","https://openalex.org/W2194775991","https://openalex.org/W2531409750","https://openalex.org/W2603777577","https://openalex.org/W2982058372","https://openalex.org/W3034713808","https://openalex.org/W3034900344","https://openalex.org/W3138516171","https://openalex.org/W3149860822","https://openalex.org/W3162850984","https://openalex.org/W3172431060","https://openalex.org/W3174656926","https://openalex.org/W3175215201","https://openalex.org/W3176241004","https://openalex.org/W3177027279","https://openalex.org/W4210623456","https://openalex.org/W4226291055","https://openalex.org/W4287758545","https://openalex.org/W4287888931","https://openalex.org/W4297095254","https://openalex.org/W4312388562","https://openalex.org/W4312732149","https://openalex.org/W4312933868","https://openalex.org/W4316660967","https://openalex.org/W4386275888","https://openalex.org/W4388430825","https://openalex.org/W6639480849","https://openalex.org/W6677618333","https://openalex.org/W6762718338","https://openalex.org/W6775993988","https://openalex.org/W6779823529","https://openalex.org/W6783713337","https://openalex.org/W6784810453","https://openalex.org/W6791353385","https://openalex.org/W6802713863"],"related_works":["https://openalex.org/W3082059448","https://openalex.org/W4313640622","https://openalex.org/W4389474468","https://openalex.org/W4300172004","https://openalex.org/W4321649381","https://openalex.org/W2997645659","https://openalex.org/W3180787869","https://openalex.org/W3203792196","https://openalex.org/W2955455867","https://openalex.org/W4295929828"],"abstract_inverted_index":{"To":[0],"make":[1],"deepfake":[2,130,153],"detectors":[3,138],"generalizable":[4],"to":[5,13,22,89,127],"different":[6],"target":[7,24,90,95,115],"domains,":[8],"one":[9],"effective":[10],"way":[11],"is":[12,85],"let":[14],"the":[15,23,31,34,53,59,70,92,99,107,114,120,137,157,168],"source":[16,88],"domain":[17,25,37,50,55,72,121],"for":[18,26,91],"training":[19],"be":[20],"similar":[21],"detection.":[27],"This":[28],"letter":[29],"tackles":[30],"problem":[32],"from":[33,87],"perspective":[35],"of":[36,61,94,101,106],"adaptation":[38],"and":[39,43,66,69,80],"achieves":[40],"both":[41],"image-level":[42,54],"feature-level":[44,71],"domains":[45],"alignments.":[46],"The":[47,83,104],"proposed":[48,169],"unsupervised":[49],"adapter":[51,122],"accomplishes":[52],"alignment":[56,73],"relying":[57,74],"on":[58,75,146,156],"combination":[60],"cross-domain":[62],"style":[63,84],"feature":[64,125],"mixing":[65],"diffusion":[67],"model,":[68],"prototypical":[76,116],"consistency":[77],"guided":[78],"supervision":[79],"adversarial":[81],"learning.":[82],"transferred":[86],"generation":[93],"data":[96],"proxy":[97],"in":[98,143,173],"form":[100],"stylized":[102,108],"images.":[103],"features":[105],"images":[109],"are":[110],"further":[111,150],"aligned":[112],"with":[113,160,164],"features.":[117],"We":[118,149],"apply":[119],"as":[123],"a":[124,140,152],"booster":[126],"four":[128],"current":[129],"detectors.":[131],"Experimental":[132],"results":[133],"show":[134],"that":[135],"all":[136,174],"get":[139],"significant":[141],"increase":[142],"AUC":[144],"values":[145],"cross-dataset":[147],"testings.":[148],"propose":[151],"detector":[154,170],"based":[155],"Xception":[158],"backbone":[159],"our":[161],"booster.":[162],"Compared":[163],"five":[165],"state-of-the-art":[166],"detectors,":[167],"performs":[171],"best":[172],"experiments.":[175]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}