{"id":"https://openalex.org/W7141584614","doi":"https://doi.org/10.48550/arxiv.2603.25140","title":"SAVe: Self-Supervised Audio-visual Deepfake Detection Exploiting Visual Artifacts and Audio-visual Misalignment","display_name":"SAVe: Self-Supervised Audio-visual Deepfake Detection Exploiting Visual Artifacts and Audio-visual Misalignment","publication_year":2026,"publication_date":"2026-03-26","ids":{"openalex":"https://openalex.org/W7141584614","doi":"https://doi.org/10.48550/arxiv.2603.25140"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.25140","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.25140","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.25140","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Shahzad, Sahibzada Adil","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Shahzad, Sahibzada Adil","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Hashmi, Ammarah","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hashmi, Ammarah","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Yamagishi, Junichi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yamagishi, Junichi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Yasuda, Yusuke","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yasuda, Yusuke","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Tsao, Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tsao, Yu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Lin, Chia-Wen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Chia-Wen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Peng, Yan-Tsung","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peng, Yan-Tsung","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Wang, Hsin-Min","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Hsin-Min","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"corresponding_author_ids":[],"corresponding_institution_ids":[],"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":null,"last_page":null},"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":0.9089000225067139,"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":0.9089000225067139,"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":0.02280000038444996,"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/T10860","display_name":"Speech and Audio Processing","score":0.021700000390410423,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/robustness","display_name":"Robustness (evolution)","score":0.7465999722480774},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6812999844551086},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.5842000246047974},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43470001220703125},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.40849998593330383},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.4036000072956085},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.37209999561309814},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36559998989105225}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7991999983787537},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7465999722480774},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6812999844551086},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6804999709129333},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.5842000246047974},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43470001220703125},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.40849998593330383},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.4036000072956085},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40209999680519104},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39070001244544983},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.37209999561309814},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36559998989105225},{"id":"https://openalex.org/C2778562939","wikidata":"https://www.wikidata.org/wiki/Q1298791","display_name":"Synchronization (alternating current)","level":3,"score":0.35760000348091125},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3562999963760376},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.35260000824928284},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3375000059604645},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.33009999990463257},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.3140000104904175},{"id":"https://openalex.org/C111370547","wikidata":"https://www.wikidata.org/wiki/Q7451120","display_name":"Sensory cue","level":2,"score":0.2921000123023987},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2840000092983246},{"id":"https://openalex.org/C2779679900","wikidata":"https://www.wikidata.org/wiki/Q25304431","display_name":"Saliency map","level":3,"score":0.2736999988555908},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.2590000033378601}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.25140","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.25140","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.25140","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.25140","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"score":0.4060235023498535,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multimodal":[0],"deepfakes":[1],"can":[2,28],"exhibit":[3],"subtle":[4],"visual":[5,73],"artifacts":[6],"and":[7,31,36,105,111],"cross-modal":[8,81],"inconsistencies,":[9],"which":[10],"remain":[11],"challenging":[12],"to":[13,38,63,70],"detect,":[14],"especially":[15],"when":[16],"detectors":[17],"are":[18],"trained":[19],"primarily":[20],"on":[21,53,103],"curated":[22],"synthetic":[23,26],"forgeries.":[24,101],"Such":[25],"dependence":[27],"introduce":[29],"dataset":[30],"generator":[32],"bias,":[33],"limiting":[34],"scalability":[35],"robustness":[37],"unseen":[39],"manipulations.":[40],"We":[41],"propose":[42],"SAVe,":[43],"a":[44,119],"self-supervised":[45,116],"audio-visual":[46,90,100],"deepfake":[47,124],"detection":[48],"framework":[49],"that":[50,93],"learns":[51],"entirely":[52],"authentic":[54],"videos.":[55],"SAVe":[56,83],"generates":[57],"on-the-fly,":[58],"identity-preserving,":[59],"region-aware":[60],"self-blended":[61],"pseudo-manipulations":[62],"emulate":[64],"tampering":[65],"artifacts,":[66],"enabling":[67],"the":[68],"model":[69],"learn":[71],"complementary":[72],"cues":[74],"across":[75],"multiple":[76],"facial":[77],"granularities.":[78],"To":[79],"capture":[80],"evidence,":[82],"also":[84],"models":[85],"lip-speech":[86],"synchronization":[87],"via":[88],"an":[89],"alignment":[91],"component":[92],"detects":[94],"temporal":[95],"misalignment":[96],"patterns":[97],"characteristic":[98],"of":[99],"Experiments":[102],"FakeAVCeleb":[104],"AV-LipSync-TIMIT":[106],"demonstrate":[107],"competitive":[108],"in-domain":[109],"performance":[110],"strong":[112],"cross-dataset":[113],"generalization,":[114],"highlighting":[115],"learning":[117],"as":[118],"scalable":[120],"paradigm":[121],"for":[122],"multimodal":[123],"detection.":[125]},"counts_by_year":[],"updated_date":"2026-03-28T08:17:26.163206","created_date":"2026-02-24T00:00:00"}
