{"id":"https://openalex.org/W4401072578","doi":"https://doi.org/10.1109/tifs.2024.3435440","title":"Fine-Grained Open-Set Deepfake Detection via Unsupervised Domain Adaptation","display_name":"Fine-Grained Open-Set Deepfake Detection via Unsupervised Domain Adaptation","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4401072578","doi":"https://doi.org/10.1109/tifs.2024.3435440"},"language":"en","primary_location":{"id":"doi:10.1109/tifs.2024.3435440","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2024.3435440","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"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 Transactions on Information Forensics and Security","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":"https://openalex.org/A5104313565","display_name":"Xinye Zhou","orcid":"https://orcid.org/0009-0003-7716-5698"},"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"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinye Zhou","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0003-7716-5698","affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091049278","display_name":"Hu Han","orcid":"https://orcid.org/0000-0001-6010-1792"},"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"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hu Han","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-6010-1792","affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050297728","display_name":"Shiguang Shan","orcid":"https://orcid.org/0000-0002-8348-392X"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiguang Shan","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-8348-392X","affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083420537","display_name":"Xilin Chen","orcid":"https://orcid.org/0000-0003-3024-4404"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xilin Chen","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-3024-4404","affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.8093,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.85914591,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"19","issue":null,"first_page":"7536","last_page":"7547"},"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":0.9965000152587891,"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":0.9965000152587891,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9957000017166138,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9941999912261963,"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":0.8441528677940369},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.6014239192008972},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5892021656036377},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.49502915143966675},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4900745153427124},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3933802545070648},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3267754018306732}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8441528677940369},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.6014239192008972},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5892021656036377},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.49502915143966675},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4900745153427124},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3933802545070648},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3267754018306732},{"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/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tifs.2024.3435440","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2024.3435440","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"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 Transactions on Information Forensics and Security","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6499999761581421,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[{"id":"https://openalex.org/G3262489766","display_name":null,"funder_award_id":"62176249","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":72,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1987971958","https://openalex.org/W1994616650","https://openalex.org/W1999668761","https://openalex.org/W2071949631","https://openalex.org/W2194775991","https://openalex.org/W2299668505","https://openalex.org/W2301937176","https://openalex.org/W2312004824","https://openalex.org/W2605488490","https://openalex.org/W2770645414","https://openalex.org/W2779610669","https://openalex.org/W2798593490","https://openalex.org/W2808631503","https://openalex.org/W2888519208","https://openalex.org/W2942074357","https://openalex.org/W2944294033","https://openalex.org/W2948429981","https://openalex.org/W2948447329","https://openalex.org/W2959409678","https://openalex.org/W2960274051","https://openalex.org/W2963118547","https://openalex.org/W2982058372","https://openalex.org/W2984700035","https://openalex.org/W2989505547","https://openalex.org/W2998158928","https://openalex.org/W3034196597","https://openalex.org/W3034371424","https://openalex.org/W3034500918","https://openalex.org/W3034521057","https://openalex.org/W3034600949","https://openalex.org/W3035436173","https://openalex.org/W3035574324","https://openalex.org/W3081492798","https://openalex.org/W3086519949","https://openalex.org/W3101631197","https://openalex.org/W3103617265","https://openalex.org/W3118608800","https://openalex.org/W3121614789","https://openalex.org/W3123001214","https://openalex.org/W3174508664","https://openalex.org/W3183999072","https://openalex.org/W3188897163","https://openalex.org/W3195059668","https://openalex.org/W3205314902","https://openalex.org/W3205880411","https://openalex.org/W4214680478","https://openalex.org/W4225966148","https://openalex.org/W4287026043","https://openalex.org/W4287080402","https://openalex.org/W4312388562","https://openalex.org/W4312443924","https://openalex.org/W4386071484","https://openalex.org/W4386071537","https://openalex.org/W4386071642","https://openalex.org/W4391406907","https://openalex.org/W4391454342","https://openalex.org/W6600949241","https://openalex.org/W6631190155","https://openalex.org/W6637131181","https://openalex.org/W6637568146","https://openalex.org/W6639480849","https://openalex.org/W6697673422","https://openalex.org/W6720691552","https://openalex.org/W6740005241","https://openalex.org/W6767264202","https://openalex.org/W6767471576","https://openalex.org/W6771956660","https://openalex.org/W6779064158","https://openalex.org/W6787972765","https://openalex.org/W6788564117","https://openalex.org/W6799942944"],"related_works":["https://openalex.org/W4394775207","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","https://openalex.org/W3156096827"],"abstract_inverted_index":{"Deepfake":[0],"represented":[1],"by":[2,172],"face":[3,6,17,24],"swapping":[4],"and":[5,12,73,157,203,246,263],"reenactment":[7],"can":[8],"transfer":[9],"the":[10,33,118,126,134,138,154,174,179,184,190,200,207,221,226,229,260],"appearance":[11],"behavioral":[13],"expressions":[14],"of":[15,35,71,128,199,206,228],"a":[16,26,141,159],"in":[18,25,81,88,94,133,153,183,220,267],"one":[19],"video":[20],"image":[21],"to":[22,53,68,86,124,149,163,210,215],"another":[23],"different":[27,79,130],"video.":[28],"In":[29,96],"recent":[30],"years,":[31],"with":[32,90,178],"advancement":[34],"deep":[36],"learning":[37],"techniques,":[38],"deepfake":[39,55,63,92,109,131,170,181,193,217,236,242,270],"technology":[40],"has":[41,254],"developed":[42],"rapidly,":[43],"achieving":[44],"increasingly":[45],"realistic":[46],"effects.":[47],"Therefore,":[48],"many":[49],"researchers":[50],"have":[51],"begun":[52],"study":[54],"detection":[56,64,194,237],"research.":[57],"However,":[58],"most":[59],"existing":[60],"studies":[61],"on":[62,240],"are":[65],"mainly":[66],"limited":[67],"binary":[69],"classification":[70],"real":[72],"fake":[74],"images,":[75],"rather":[76],"than":[77,259],"identifying":[78],"methods":[80,132],"an":[82,101],"open-world":[83],"scenario,":[84],"leading":[85],"failures":[87],"dealing":[89],"unknown":[91,169,216],"categories":[93,171,182],"practice.":[95],"this":[97],"paper,":[98],"we":[99,188],"propose":[100],"unsupervised":[102],"domain":[103,120,156,202,209,256],"adaptation":[104],"method":[105,112,139,231,253],"for":[106,121,168],"fine-grained":[107,235,268],"open-set":[108,234,269],"detection.":[110,271],"Our":[111],"first":[113],"uses":[114,140],"labeled":[115,197],"data":[116,198,205],"from":[117],"source":[119,135,185,201],"model":[122,195],"pre-training":[123],"establish":[125],"ability":[127,214,258],"recognizing":[129],"domain.":[136,186,223],"Then,":[137],"Network":[142],"Memorization":[143],"based":[144,239],"Adaptive":[145],"Clustering":[146],"(NMAC)":[147],"approach":[148],"cluster":[150],"unlabeled":[151],"images":[152],"target":[155,208,222],"designs":[158],"Pseudo-Label":[160],"Generation":[161],"(PLG)":[162],"generate":[164],"virtual":[165],"class":[166],"labels":[167],"matching":[173],"adaptive":[175],"clustering":[176],"results":[177,249],"known":[180],"Finally,":[187],"retrain":[189],"initial":[191],"multi-class":[192],"using":[196],"pseudo-labeled":[204],"improve":[211],"its":[212],"generalization":[213,257],"classes":[218],"presented":[219],"We":[224],"validate":[225],"effectiveness":[227],"proposed":[230],"under":[232],"multiple":[233],"tasks":[238],"three":[241],"datasets":[243],"(ForgerNet,":[244],"FaceForensics++,":[245],"FakeAVCeleb).":[247],"Experimental":[248],"show":[250],"that":[251],"our":[252],"better":[255],"state-of-the-art":[261],"methods,":[262],"achieves":[264],"promising":[265],"performance":[266]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}