{"id":"https://openalex.org/W7130736605","doi":"https://doi.org/10.48550/arxiv.2602.17260","title":"EA-Swin: An Embedding-Agnostic Swin Transformer for AI-Generated Video Detection","display_name":"EA-Swin: An Embedding-Agnostic Swin Transformer for AI-Generated Video Detection","publication_year":2026,"publication_date":"2026-02-19","ids":{"openalex":"https://openalex.org/W7130736605","doi":"https://doi.org/10.48550/arxiv.2602.17260"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2602.17260","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.17260","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.2602.17260","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126498722","display_name":"Hung Mai","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Mai, Hung","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110380954","display_name":"Long Dinh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dinh, Loi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126510028","display_name":"Duc Hai Nguyen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nguyen, Duc Hai","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028716440","display_name":"Dat Do","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Do, Dat","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126463256","display_name":"Luong Doan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Doan, Luong","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126518664","display_name":"Khanh Nguyen Quoc","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Quoc, Khanh Nguyen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126472503","display_name":"Huan Vu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vu, Huan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Islam, Naeem Ul","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Islam, Naeem Ul","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Do, Tuan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Do, Tuan","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5126498722"],"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":0.42980000376701355,"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":0.42980000376701355,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.16820000112056732,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.08829999715089798,"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/embedding","display_name":"Embedding","score":0.7152000069618225},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.6593999862670898},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.6273999810218811},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.57669997215271},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.49059998989105225},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4478999972343445}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.715499997138977},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7152000069618225},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6593999862670898},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.6273999810218811},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.57669997215271},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.529699981212616},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.49059998989105225},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4478999972343445},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.42969998717308044},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.362199991941452},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3346000015735626},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.31709998846054077},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3012000024318695},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3009999990463257},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2630999982357025},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2630000114440918}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2602.17260","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.17260","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.2602.17260","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.17260","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2],"foundation":[3],"video":[4,53,142],"generators":[5,95],"such":[6],"as":[7],"Sora2,":[8],"Veo3,":[9],"and":[10,93,96,136],"other":[11],"commercial":[12,92],"systems":[13],"have":[14],"produced":[15],"highly":[16],"realistic":[17],"synthetic":[18],"videos,":[19],"exposing":[20],"the":[21,72],"limitations":[22],"of":[23,124],"existing":[24,88],"detection":[25],"methods":[26,118],"that":[27,46,81,107],"rely":[28],"on":[29,51],"shallow":[30],"embedding":[31],"trajectories,":[32],"image-based":[33],"adaptation,":[34],"or":[35],"computationally":[36],"heavy":[37],"MLLMs.":[38],"We":[39],"propose":[40],"EA-Swin,":[41],"an":[42],"Embedding-Agnostic":[43],"Swin":[44],"Transformer":[45],"models":[47],"spatiotemporal":[48],"dependencies":[49],"directly":[50],"pretrained":[52],"embeddings":[54],"via":[55],"a":[56,75,122,134],"factorized":[57],"windowed":[58],"attention":[59],"design,":[60],"making":[61],"it":[62],"compatible":[63],"with":[64,86],"generic":[65],"ViT-style":[66],"patch-based":[67],"encoders.":[68],"Moreover,":[69],"we":[70],"construct":[71],"EA-Video":[73],"dataset,":[74],"benchmark":[76],"dataset":[77],"comprising":[78],"130K":[79],"videos":[80],"integrates":[82],"newly":[83],"collected":[84],"samples":[85],"curated":[87],"datasets,":[89],"covering":[90],"diverse":[91],"open-source":[94],"including":[97],"unseen-generator":[98],"splits":[99],"for":[100,139],"rigorous":[101],"cross-distribution":[102],"evaluation.":[103],"Extensive":[104],"experiments":[105],"show":[106],"EA-Swin":[108],"achieves":[109],"0.97-0.99":[110],"accuracy":[111],"across":[112],"major":[113],"generators,":[114],"outperforming":[115],"prior":[116],"SoTA":[117],"(typically":[119],"0.8-0.9)":[120],"by":[121],"margin":[123],"5-20\\%,":[125],"while":[126],"maintaining":[127],"strong":[128],"generalization":[129],"to":[130],"unseen":[131],"distributions,":[132],"establishing":[133],"scalable":[135],"robust":[137],"solution":[138],"modern":[140],"AI-generated":[141],"detection.":[143]},"counts_by_year":[],"updated_date":"2026-03-25T23:56:10.502304","created_date":"2026-02-21T00:00:00"}
