{"id":"https://openalex.org/W4417086475","doi":"https://doi.org/10.48550/arxiv.2512.04175","title":"Beyond Flicker: Detecting Kinematic Inconsistencies for Generalizable Deepfake Video Detection","display_name":"Beyond Flicker: Detecting Kinematic Inconsistencies for Generalizable Deepfake Video Detection","publication_year":2025,"publication_date":"2025-12-03","ids":{"openalex":"https://openalex.org/W4417086475","doi":"https://doi.org/10.48550/arxiv.2512.04175"},"language":null,"primary_location":{"id":"pmh:oai:arXiv.org:2512.04175","is_oa":true,"landing_page_url":"https://arxiv.org/abs/2512.04175","pdf_url":"https://arxiv.org/pdf/2512.04175","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2512.04175","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5093675155","display_name":"Alejandro Cobo","orcid":"https://orcid.org/0009-0007-7967-6837"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cobo, Alejandro","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039846176","display_name":"Roberto Valle","orcid":"https://orcid.org/0000-0003-1423-1478"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Valle, Roberto","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034180773","display_name":"Jos\u00e9 M. Buenaposada","orcid":"https://orcid.org/0000-0002-4308-9653"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Buenaposada, Jos\u00e9 Miguel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5014943420","display_name":"Luis Baumela","orcid":"https://orcid.org/0000-0001-6910-4359"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Baumela, Luis","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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":0.7804999947547913,"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":0.7804999947547913,"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/T11448","display_name":"Face recognition and analysis","score":0.20110000669956207,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.0019000000320374966,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.708899974822998},{"id":"https://openalex.org/keywords/kinematics","display_name":"Kinematics","score":0.7081000208854675},{"id":"https://openalex.org/keywords/landmark","display_name":"Landmark","score":0.6582000255584717},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.6144000291824341},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.6083999872207642},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.6075000166893005},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5741999745368958},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4700999855995178},{"id":"https://openalex.org/keywords/natural","display_name":"Natural (archaeology)","score":0.4397999942302704}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7997999787330627},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7436000108718872},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.708899974822998},{"id":"https://openalex.org/C39920418","wikidata":"https://www.wikidata.org/wiki/Q11476","display_name":"Kinematics","level":2,"score":0.7081000208854675},{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.6582000255584717},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.6144000291824341},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.6083999872207642},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.6075000166893005},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5831999778747559},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5741999745368958},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4700999855995178},{"id":"https://openalex.org/C2776608160","wikidata":"https://www.wikidata.org/wiki/Q4785462","display_name":"Natural (archaeology)","level":2,"score":0.4397999942302704},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.4104999899864197},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3912000060081482},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3774000108242035},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.3199000060558319},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.31709998846054077},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.3075000047683716},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.29649999737739563},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2948000133037567},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.2784000039100647},{"id":"https://openalex.org/C2780624872","wikidata":"https://www.wikidata.org/wiki/Q852453","display_name":"Motion detection","level":3,"score":0.26919999718666077},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C20864712","wikidata":"https://www.wikidata.org/wiki/Q667800","display_name":"Biological motion","level":3,"score":0.2551000118255615},{"id":"https://openalex.org/C48007421","wikidata":"https://www.wikidata.org/wiki/Q676252","display_name":"Motion capture","level":3,"score":0.25440001487731934}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2512.04175","is_oa":true,"landing_page_url":"https://arxiv.org/abs/2512.04175","pdf_url":"https://arxiv.org/pdf/2512.04175","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2512.04175","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2512.04175","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2512.04175","is_oa":true,"landing_page_url":"https://arxiv.org/abs/2512.04175","pdf_url":"https://arxiv.org/pdf/2512.04175","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4417086475.pdf","grobid_xml":"https://content.openalex.org/works/W4417086475.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Generalizing":[0],"deepfake":[1],"detection":[2],"to":[3,13,18,33,45,97,135],"unseen":[4],"manipulations":[5],"remains":[6],"a":[7,20,62,80],"key":[8,63],"challenge.":[9],"A":[10,128],"recent":[11],"approach":[12],"tackle":[14],"this":[15,44,76],"issue":[16],"is":[17,49],"train":[19,94],"network":[21,129],"with":[22,30,89],"pristine":[23,123],"face":[24,126],"images":[25],"that":[26,85],"have":[27],"been":[28],"manipulated":[29],"hand-crafted":[31],"artifacts":[32,57,121],"extract":[34],"more":[35],"generalizable":[36],"clues.":[37],"While":[38],"effective":[39],"for":[40],"static":[41],"images,":[42],"extending":[43],"the":[46,65,112],"video":[47,82],"domain":[48],"an":[50,95],"open":[51],"issue.":[52],"Existing":[53],"methods":[54],"model":[55],"temporal":[56],"as":[58],"frame-to-frame":[59],"instabilities,":[60],"overlooking":[61],"vulnerability:":[64],"violation":[66],"of":[67],"natural":[68,113],"motion":[69,103],"dependencies":[70],"between":[71],"different":[72],"facial":[73,99,116],"regions.":[74],"In":[75],"paper,":[77],"we":[78,109],"propose":[79],"synthetic":[81],"generation":[83],"method":[84],"creates":[86],"training":[87],"data":[88,133],"subtle":[90],"kinematic":[91],"inconsistencies.":[92],"We":[93],"autoencoder":[96],"decompose":[98],"landmark":[100],"configurations":[101],"into":[102,122],"bases.":[104],"By":[105],"manipulating":[106],"these":[107,120,137],"bases,":[108],"selectively":[110],"break":[111],"correlations":[114],"in":[115],"movements":[117],"and":[118],"introduce":[119],"videos":[124],"via":[125],"morphing.":[127],"trained":[130],"on":[131,145],"our":[132],"learns":[134],"spot":[136],"sophisticated":[138],"biomechanical":[139],"flaws,":[140],"achieving":[141],"state-of-the-art":[142],"generalization":[143],"results":[144],"several":[146],"popular":[147],"benchmarks.":[148]},"counts_by_year":[],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2025-12-06T00:00:00"}