{"id":"https://openalex.org/W4377236452","doi":"https://doi.org/10.1145/3581807.3581847","title":"Video Forgery Detection Using Spatio-Temporal Dual Transformer","display_name":"Video Forgery Detection Using Spatio-Temporal Dual Transformer","publication_year":2022,"publication_date":"2022-11-17","ids":{"openalex":"https://openalex.org/W4377236452","doi":"https://doi.org/10.1145/3581807.3581847"},"language":"en","primary_location":{"id":"doi:10.1145/3581807.3581847","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581807.3581847","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 11th International Conference on Computing and Pattern Recognition","raw_type":"proceedings-article"},"type":"conference-paper","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/A5103149988","display_name":"Chenyu Liu","orcid":"https://orcid.org/0000-0003-1139-7392"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenyu Liu","raw_affiliation_strings":["Center for Research on IntelligentPerception and Computing, Institute of Automation, Chinese Academy of Sciences, China"],"raw_orcid":"https://orcid.org/0000-0003-1139-7392","affiliations":[{"raw_affiliation_string":"Center for Research on IntelligentPerception and Computing, Institute of Automation, Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054585200","display_name":"Jia Li","orcid":"https://orcid.org/0000-0002-6077-7896"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jia Li","raw_affiliation_strings":["Center for Research on IntelligentPerception and Computing, Institute of Automation, Chinese Academy of Sciences, China"],"raw_orcid":"https://orcid.org/0000-0002-6077-7896","affiliations":[{"raw_affiliation_string":"Center for Research on IntelligentPerception and Computing, Institute of Automation, Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047230227","display_name":"Junxian Duan","orcid":"https://orcid.org/0000-0002-0218-6924"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junxian Duan","raw_affiliation_strings":["Center for Research on IntelligentPerception and Computing, Institute of Automation, Chinese Academy of Sciences, China"],"raw_orcid":"https://orcid.org/0000-0002-0218-6924","affiliations":[{"raw_affiliation_string":"Center for Research on IntelligentPerception and Computing, Institute of Automation, Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005195235","display_name":"Huaibo Huang","orcid":"https://orcid.org/0000-0001-5866-2283"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huaibo Huang","raw_affiliation_strings":["Center for Research on IntelligentPerception and Computing, Institute of Automation, Chinese Academy of Sciences, China"],"raw_orcid":"https://orcid.org/0000-0001-5866-2283","affiliations":[{"raw_affiliation_string":"Center for Research on IntelligentPerception and Computing, Institute of Automation, Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"273","last_page":"281"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9994000196456909,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9994000196456909,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9993000030517578,"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":0.9986000061035156,"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":0.7981448173522949},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7164208889007568},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.6235174536705017},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5651799440383911},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5468024015426636},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.5237060785293579},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.48787569999694824},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41628673672676086},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.13783559203147888}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7981448173522949},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7164208889007568},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.6235174536705017},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5651799440383911},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5468024015426636},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.5237060785293579},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.48787569999694824},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41628673672676086},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.13783559203147888},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3581807.3581847","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581807.3581847","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 11th International Conference on Computing and Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.47999998927116394,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":61,"referenced_works":["https://openalex.org/W2017674864","https://openalex.org/W2046943827","https://openalex.org/W2152766492","https://openalex.org/W2341528187","https://openalex.org/W2531409750","https://openalex.org/W2609296554","https://openalex.org/W2612690371","https://openalex.org/W2737804889","https://openalex.org/W2750772846","https://openalex.org/W2752782242","https://openalex.org/W2766527293","https://openalex.org/W2773031116","https://openalex.org/W2811414481","https://openalex.org/W2811432216","https://openalex.org/W2891145043","https://openalex.org/W2898877033","https://openalex.org/W2902930830","https://openalex.org/W2904367110","https://openalex.org/W2904996883","https://openalex.org/W2911424785","https://openalex.org/W2912336782","https://openalex.org/W2913688275","https://openalex.org/W2945262873","https://openalex.org/W2946948417","https://openalex.org/W2956958106","https://openalex.org/W2962770929","https://openalex.org/W2969104300","https://openalex.org/W2969985801","https://openalex.org/W2976627522","https://openalex.org/W2995516027","https://openalex.org/W2998068861","https://openalex.org/W3033696290","https://openalex.org/W3034577585","https://openalex.org/W3034785167","https://openalex.org/W3042844210","https://openalex.org/W3048341421","https://openalex.org/W3080658511","https://openalex.org/W3101998545","https://openalex.org/W3108281670","https://openalex.org/W3120504414","https://openalex.org/W3135723753","https://openalex.org/W3136741409","https://openalex.org/W3138202081","https://openalex.org/W3138516171","https://openalex.org/W3177525997","https://openalex.org/W3207556837","https://openalex.org/W3217362056","https://openalex.org/W4230100295","https://openalex.org/W4236716275","https://openalex.org/W4238416801","https://openalex.org/W4241001320","https://openalex.org/W4244098250","https://openalex.org/W4244186786","https://openalex.org/W4247924304","https://openalex.org/W4286696412","https://openalex.org/W4289106821","https://openalex.org/W6688299585","https://openalex.org/W6767924615","https://openalex.org/W6772330936","https://openalex.org/W6785411885","https://openalex.org/W6791449262"],"related_works":["https://openalex.org/W2601157893","https://openalex.org/W2131735617","https://openalex.org/W2373006798","https://openalex.org/W2056912418","https://openalex.org/W2123759770","https://openalex.org/W2033213769","https://openalex.org/W2811390910","https://openalex.org/W4312376745","https://openalex.org/W2082269393","https://openalex.org/W2043960970"],"abstract_inverted_index":{"The":[0],"fake":[1,21,63,87,114],"videos":[2,64,88,228],"generated":[3],"by":[4],"deep":[5],"generation":[6],"technology":[7],"pose":[8],"a":[9,121,162,187],"potential":[10],"threat":[11],"to":[12,19,34,94,141,150,166,168,181,192,212,225,230],"social":[13],"stability,":[14],"which":[15],"makes":[16],"it":[17],"critical":[18],"detect":[20],"videos.":[22,97],"Although":[23],"the":[24,32,53,56,60,70,74,78,82,86,95,99,103,109,113,135,183,194,203,227,231,252,261],"previous":[25],"detection":[26,129],"methods":[27],"have":[28],"achieved":[29],"high":[30,256],"accuracy,":[31],"generalization":[33],"different":[35],"datasets":[36,240],"and":[37,49,62,157,202,216,246,258],"in":[38,198],"realistic":[39],"scenes":[40],"is":[41,147,190,210,223],"not":[42],"effective.":[43],"We":[44,160,235],"find":[45],"several":[46],"novel":[47],"temporal":[48,136,196],"spatial":[50,152],"clues.":[51],"In":[52,73],"frequency":[54],"domain,":[55],"inter-frame":[57,199],"differences":[58],"between":[59],"real":[61,96,104],"are":[65],"significantly":[66],"more":[67,90,170],"obvious":[68],"than":[69],"intra-frame":[71],"differences.":[72],"shallow":[75,155],"texture":[76],"on":[77,239],"CbCr":[79],"color":[80],"channels,":[81],"forged":[83],"areas":[84],"of":[85,102,112,138,154],"appear":[89],"distinct":[91],"blurring":[92],"compared":[93],"And":[98],"optical":[100,110,204],"flow":[101,111],"video":[105,115,127],"changes":[106,116],"gradually,":[107],"while":[108],"drastically.":[117],"This":[118],"paper":[119],"proposes":[120],"spatio-temporal":[122,132,233],"dual":[123],"Transformer":[124,189,222],"network":[125],"for":[126],"forgery":[128],"that":[130,251],"integrates":[131],"clues":[133],"with":[134],"consistency":[137],"consecutive":[139],"frames":[140],"improve":[142],"generalization.":[143],"Specifically,":[144],"an":[145,178],"EfficientNet":[146,167],"first":[148],"used":[149,191,224],"extract":[151,169],"artifacts":[153,197],"textures":[156],"high-frequency":[158],"information.":[159],"add":[161],"new":[163],"loss":[164],"function":[165],"robust":[171],"face":[172],"features,":[173],"as":[174,176,242],"well":[175],"introduce":[177],"attention":[179],"mechanism":[180],"enhance":[182],"extracted":[184,232],"features.":[185,234],"Next,":[186],"Swin":[188,221],"capture":[193],"subtle":[195],"spectrum":[200],"difference":[201],"flow.":[205],"A":[206],"feature":[207],"interaction":[208],"module":[209],"added":[211],"fuse":[213],"local":[214],"features":[215],"global":[217],"representations.":[218],"Finally,":[219],"another":[220],"classify":[226],"according":[229],"evaluate":[236],"our":[237],"method":[238],"such":[241],"FaceForensics++,":[243],"Celeb-DF":[244],"(v2)":[245],"DFDC.":[247],"Extensive":[248],"experiments":[249],"show":[250],"proposed":[253],"framework":[254],"has":[255],"accuracy":[257],"generalization,":[259],"outperforming":[260],"current":[262],"state-of-the-art":[263],"methods.":[264]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}