{"id":"https://openalex.org/W7127040948","doi":"https://doi.org/10.1145/3784833.3784856","title":"Deepfake Image Detection: A Universal Approach via Vision-Language Models","display_name":"Deepfake Image Detection: A Universal Approach via Vision-Language Models","publication_year":2025,"publication_date":"2025-11-12","ids":{"openalex":"https://openalex.org/W7127040948","doi":"https://doi.org/10.1145/3784833.3784856"},"language":null,"primary_location":{"id":"doi:10.1145/3784833.3784856","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3784833.3784856","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 11th International Conference on Communication and Information Processing","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3784833.3784856","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5124725334","display_name":"Xiangli Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangli Zhang","raw_affiliation_strings":["Guilin University of Electronic Technology, Guilin, China"],"raw_orcid":"https://orcid.org/0009-0008-0140-3019","affiliations":[{"raw_affiliation_string":"Guilin University of Electronic Technology, Guilin, China","institution_ids":["https://openalex.org/I5343935"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124714454","display_name":"Junjie Huo","orcid":null},"institutions":[{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junjie Huo","raw_affiliation_strings":["Guilin University of Electronic Technology, Guilin, China"],"raw_orcid":"https://orcid.org/0009-0002-0712-1633","affiliations":[{"raw_affiliation_string":"Guilin University of Electronic Technology, Guilin, China","institution_ids":["https://openalex.org/I5343935"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124735735","display_name":"Hongmei Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongmei Zhang","raw_affiliation_strings":["Guilin University of Electronic Technology, Guilin, China"],"raw_orcid":"https://orcid.org/0000-0003-0608-4498","affiliations":[{"raw_affiliation_string":"Guilin University of Electronic Technology, Guilin, China","institution_ids":["https://openalex.org/I5343935"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124716860","display_name":"Qingye Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingye Zhou","raw_affiliation_strings":["Guilin University of Electronic Technology, Guilin, China"],"raw_orcid":"https://orcid.org/0009-0003-8126-5288","affiliations":[{"raw_affiliation_string":"Guilin University of Electronic Technology, Guilin, China","institution_ids":["https://openalex.org/I5343935"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124702740","display_name":"Hongyi Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyi Wei","raw_affiliation_strings":["Guilin University of Electronic Technology, Guilin, China"],"raw_orcid":"https://orcid.org/0009-0003-7101-0126","affiliations":[{"raw_affiliation_string":"Guilin University of Electronic Technology, Guilin, China","institution_ids":["https://openalex.org/I5343935"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124731934","display_name":"Ziyu Li","orcid":null},"institutions":[{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziyu Li","raw_affiliation_strings":["Guilin University of Electronic Technology, Guilin, China"],"raw_orcid":"https://orcid.org/0009-0006-1082-7951","affiliations":[{"raw_affiliation_string":"Guilin University of Electronic Technology, Guilin, China","institution_ids":["https://openalex.org/I5343935"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I5343935"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"53","last_page":"57"},"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":0.49790000915527344,"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":0.49790000915527344,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.2037000060081482,"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/T11147","display_name":"Misinformation and Its Impacts","score":0.06549999862909317,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6924999952316284},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.5848000049591064},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5655999779701233},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5601000189781189},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.557699978351593},{"id":"https://openalex.org/keywords/adapter","display_name":"Adapter (computing)","score":0.4271000027656555},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41600000858306885}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6970000267028809},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6924999952316284},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5956000089645386},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.5848000049591064},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5655999779701233},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5601000189781189},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.557699978351593},{"id":"https://openalex.org/C177284502","wikidata":"https://www.wikidata.org/wiki/Q1005390","display_name":"Adapter (computing)","level":2,"score":0.4271000027656555},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41600000858306885},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.3864000141620636},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3725999891757965},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3718000054359436},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3463999927043915},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3303000032901764},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3246000111103058},{"id":"https://openalex.org/C2987933465","wikidata":"https://www.wikidata.org/wiki/Q141130","display_name":"Image manipulation","level":3,"score":0.28450000286102295},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.2711000144481659},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.26759999990463257}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3784833.3784856","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3784833.3784856","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 11th International Conference on Communication and Information Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3784833.3784856","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3784833.3784856","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 11th International Conference on Communication and Information Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.707034170627594}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W3019200173","https://openalex.org/W3034577585","https://openalex.org/W3162926177","https://openalex.org/W3166396011","https://openalex.org/W4298289240","https://openalex.org/W4308234128","https://openalex.org/W4386071953","https://openalex.org/W4386075954","https://openalex.org/W4386790226","https://openalex.org/W4393154086","https://openalex.org/W4399418483","https://openalex.org/W4402716164","https://openalex.org/W4402753859"],"related_works":[],"abstract_inverted_index":{"To":[0],"address":[1],"the":[2,20,38,57,61,70,93,98,114,139],"issues":[3],"of":[4,11,42,60,97,121,130],"performance":[5],"degradation":[6],"and":[7,72,83],"insufficient":[8],"generalization":[9],"ability":[10],"deepfake":[12,25],"detection":[13,26,48],"models":[14,32,44],"when":[15],"detecting":[16],"fake":[17],"images":[18],"outside":[19],"training":[21],"distribution,":[22],"a":[23,78,84],"general":[24],"model":[27,63],"(FEFA)":[28],"based":[29],"on":[30],"vision-language":[31,43,62],"is":[33,54],"proposed,":[34],"aiming":[35],"to":[36,45,64,100,133],"leverage":[37],"zero-shot":[39],"learning":[40],"capability":[41,103],"improve":[46],"forgery":[47,66,108],"performance.":[49],"The":[50],"forgery-aware":[51],"adapter":[52],"(FAA)":[53],"integrated":[55],"into":[56,92],"image":[58,71],"encoder":[59],"extract":[65],"features":[67],"from":[68],"both":[69],"frequency":[73,79,85,94,106],"domains.":[74],"In":[75],"this":[76],"work,":[77],"band":[80],"attention":[81],"mechanism":[82],"detail":[86],"enhancement":[87],"component":[88],"are":[89],"further":[90],"incorporated":[91],"domain":[95,107],"branch":[96],"FAA":[99],"enhance":[101],"its":[102],"in":[104],"modeling":[105],"characteristics.":[109],"Experimental":[110],"results":[111],"show":[112],"that":[113],"proposed":[115],"method":[116],"achieves":[117],"an":[118,128],"average":[119],"accuracy":[120],"94.75%":[122],"across":[123],"multiple":[124],"public":[125],"datasets,":[126],"representing":[127],"improvement":[129],"10.84%":[131],"compared":[132],"current":[134],"baseline":[135],"model,":[136],"thereby":[137],"validating":[138],"model's":[140],"cross-dataset":[141],"generalization.":[142]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-02-03T00:00:00"}