{"id":"https://openalex.org/W4388189737","doi":"https://doi.org/10.1145/3581783.3612377","title":"DFIL: Deepfake Incremental Learning by Exploiting Domain-invariant Forgery Clues","display_name":"DFIL: Deepfake Incremental Learning by Exploiting Domain-invariant Forgery Clues","publication_year":2023,"publication_date":"2023-10-26","ids":{"openalex":"https://openalex.org/W4388189737","doi":"https://doi.org/10.1145/3581783.3612377"},"language":"en","primary_location":{"id":"doi:10.1145/3581783.3612377","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581783.3612377","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","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/A5012194957","display_name":"Kun Pan","orcid":"https://orcid.org/0009-0006-8931-2546"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kun Pan","raw_affiliation_strings":["Zhejiang University & ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University & ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, China","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082962427","display_name":"Yifang Yin","orcid":"https://orcid.org/0000-0002-6525-6133"},"institutions":[{"id":"https://openalex.org/I115228651","display_name":"Agency for Science, Technology and Research","ror":"https://ror.org/036wvzt09","country_code":"SG","type":"government","lineage":["https://openalex.org/I115228651"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yifang Yin","raw_affiliation_strings":["I2R, A*STAR, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"I2R, A*STAR, Singapore, Singapore","institution_ids":["https://openalex.org/I115228651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100643676","display_name":"Wei Yao","orcid":"https://orcid.org/0009-0009-4005-4410"},"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":"Yao Wei","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078406349","display_name":"Feng Lin","orcid":"https://orcid.org/0000-0001-5240-5200"},"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":"Feng Lin","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072485378","display_name":"Zhongjie Ba","orcid":"https://orcid.org/0000-0003-0921-8869"},"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":"Zhongjie Ba","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101715620","display_name":"Zhenguang Liu","orcid":"https://orcid.org/0000-0002-7981-9873"},"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":"Zhenguang Liu","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100422345","display_name":"Zhibo Wang","orcid":"https://orcid.org/0000-0002-5804-3279"},"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":"Zhibo Wang","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036908366","display_name":"Lorenzo Cavallaro","orcid":"https://orcid.org/0000-0002-3878-2680"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Lorenzo Cavallaro","raw_affiliation_strings":["University College London & Zhejiang University, London, United Kingdom"],"affiliations":[{"raw_affiliation_string":"University College London & Zhejiang University, London, United Kingdom","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000596496","display_name":"Kui Ren","orcid":"https://orcid.org/0000-0003-3441-6277"},"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":"Kui Ren","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5012194957"],"corresponding_institution_ids":["https://openalex.org/I168879160"],"apc_list":null,"apc_paid":null,"fwci":4.4678,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.95696026,"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":"8035","last_page":"8046"},"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":0.9983000159263611,"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":0.9983000159263611,"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":0.9879999756813049,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9793999791145325,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8295103311538696},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.6741248369216919},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5750930905342102},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5596538782119751},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.5113760828971863},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4713696241378784},{"id":"https://openalex.org/keywords/forgetting","display_name":"Forgetting","score":0.4708176255226135},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.46085208654403687},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.44784584641456604},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4281498193740845},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4161926805973053},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33695828914642334},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3365882635116577},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1999688744544983},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08933621644973755}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8295103311538696},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.6741248369216919},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5750930905342102},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5596538782119751},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.5113760828971863},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4713696241378784},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.4708176255226135},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.46085208654403687},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.44784584641456604},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4281498193740845},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4161926805973053},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33695828914642334},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3365882635116577},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1999688744544983},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08933621644973755},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3581783.3612377","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581783.3612377","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2051114290","display_name":null,"funder_award_id":"62172359","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":68,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2301937176","https://openalex.org/W2473930607","https://openalex.org/W2558151185","https://openalex.org/W2560647685","https://openalex.org/W2737492962","https://openalex.org/W2753311918","https://openalex.org/W2798991696","https://openalex.org/W2914447220","https://openalex.org/W2956958106","https://openalex.org/W2963072899","https://openalex.org/W2963684180","https://openalex.org/W2964189064","https://openalex.org/W2979930345","https://openalex.org/W2982058372","https://openalex.org/W2984700035","https://openalex.org/W2999368783","https://openalex.org/W3005680577","https://openalex.org/W3012033723","https://openalex.org/W3034196597","https://openalex.org/W3034552680","https://openalex.org/W3034713808","https://openalex.org/W3035309251","https://openalex.org/W3035501943","https://openalex.org/W3035524453","https://openalex.org/W3042844210","https://openalex.org/W3092709185","https://openalex.org/W3102887392","https://openalex.org/W3107810305","https://openalex.org/W3130207513","https://openalex.org/W3158353280","https://openalex.org/W3159841508","https://openalex.org/W3168149265","https://openalex.org/W3173317327","https://openalex.org/W3173415456","https://openalex.org/W3173628312","https://openalex.org/W3174508664","https://openalex.org/W3174656926","https://openalex.org/W3174917907","https://openalex.org/W3175342695","https://openalex.org/W3176241004","https://openalex.org/W3176482836","https://openalex.org/W3176990204","https://openalex.org/W3177494822","https://openalex.org/W3180392831","https://openalex.org/W3182782565","https://openalex.org/W3183999072","https://openalex.org/W3205497712","https://openalex.org/W4200635057","https://openalex.org/W4205817612","https://openalex.org/W4213222913","https://openalex.org/W4225966148","https://openalex.org/W4285606520","https://openalex.org/W4293567872","https://openalex.org/W4304084264","https://openalex.org/W4312388562","https://openalex.org/W4312753047","https://openalex.org/W4312967678","https://openalex.org/W4313118515","https://openalex.org/W4313125684","https://openalex.org/W4313177092","https://openalex.org/W4367046815","https://openalex.org/W4385570415","https://openalex.org/W6720711607","https://openalex.org/W6738602802","https://openalex.org/W6741087337","https://openalex.org/W6776700526","https://openalex.org/W6991134107"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4281702477","https://openalex.org/W2490526372","https://openalex.org/W4376166922","https://openalex.org/W4378510483","https://openalex.org/W4320853675"],"abstract_inverted_index":{"The":[0],"malicious":[1],"use":[2],"and":[3,116,132,149,170,179],"widespread":[4],"dissemination":[5],"of":[6,12,32,66,77,168,173],"deepfake":[7,15,42,67],"pose":[8],"a":[9,26,57,74,90,120],"significant":[10],"crisis":[11],"trust.":[13],"Current":[14],"detection":[16,33,68],"models":[17,34,69],"can":[18],"generally":[19],"recognize":[20],"forgery":[21],"images":[22,38],"by":[23,40,70],"training":[24],"on":[25,37,94,119,157,175],"large":[27],"dataset.":[28],"However,":[29],"the":[30,46,64,101,138,162],"accuracy":[31,172],"degrades":[35],"significantly":[36],"generated":[39],"new":[41,78,103,163],"methods":[43],"due":[44],"to":[45,88,100,128,136],"difference":[47],"in":[48,113],"data":[49,84],"distribution.":[50],"To":[51,80,105],"tackle":[52],"this":[53],"issue,":[54],"we":[55,86,109,126],"present":[56],"novel":[58],"incremental":[59],"learning":[60,72,148],"framework":[61],"that":[62],"improves":[63],"generalization":[65],"continual":[71],"from":[73],"small":[75],"number":[76],"samples.":[79],"cope":[81],"with":[82],"different":[83],"distributions,":[85],"propose":[87,127],"learn":[89],"domain-invariant":[91,146],"representation":[92,147],"based":[93,118],"supervised":[95],"contrastive":[96],"learning,":[97],"preventing":[98],"overfit":[99],"insufficient":[102],"data.":[104],"mitigate":[106],"catastrophic":[107],"forgetting,":[108],"regularize":[110],"our":[111],"model":[112],"both":[114,130,145],"feature-level":[115],"label-level":[117],"multi-perspective":[121],"knowledge":[122,151],"distillation":[123],"approach.":[124],"Finally,":[125],"select":[129],"central":[131],"hard":[133],"representative":[134],"samples":[135],"update":[137],"replay":[139],"set,":[140],"which":[141],"is":[142,183],"beneficial":[143],"for":[144],"rehearsal-based":[150],"preserving.":[152],"We":[153],"conduct":[154],"extensive":[155],"experiments":[156],"four":[158],"benchmark":[159],"datasets,":[160],"obtaining":[161],"state-of-the-art":[164],"average":[165,171],"forgetting":[166],"rate":[167],"7.01":[169],"85.49":[174],"FF++,":[176],"DFDC-P,":[177],"DFD,":[178],"CDF2.":[180],"Our":[181],"code":[182],"released":[184],"at":[185],"\\textcolorblue":[186],"https://github.com/DeepFakeIL/DFIL.":[187]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-05T09:29:38.588285","created_date":"2025-10-10T00:00:00"}