{"id":"https://openalex.org/W4283459426","doi":"https://doi.org/10.1145/3512732.3533581","title":"Uncovering the Strength of Capsule Networks in Deepfake Detection","display_name":"Uncovering the Strength of Capsule Networks in Deepfake Detection","publication_year":2022,"publication_date":"2022-06-24","ids":{"openalex":"https://openalex.org/W4283459426","doi":"https://doi.org/10.1145/3512732.3533581"},"language":"en","primary_location":{"id":"doi:10.1145/3512732.3533581","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3512732.3533581","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 1st International Workshop on Multimedia AI against Disinformation","raw_type":"proceedings-article"},"type":"article","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/A5075315087","display_name":"Dan-Cristian Stanciu","orcid":"https://orcid.org/0009-0008-4561-4328"},"institutions":[{"id":"https://openalex.org/I61641377","display_name":"Universitatea Na\u021bional\u0103 de \u0218tiin\u021b\u0103 \u0219i Tehnologie Politehnica Bucure\u0219ti","ror":"https://ror.org/0558j5q12","country_code":"RO","type":"education","lineage":["https://openalex.org/I61641377"]}],"countries":["RO"],"is_corresponding":true,"raw_author_name":"Dan-Cristian Stanciu","raw_affiliation_strings":["Politehnica University of Bucharest, Bucharest, Romania"],"affiliations":[{"raw_affiliation_string":"Politehnica University of Bucharest, Bucharest, Romania","institution_ids":["https://openalex.org/I61641377"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051234459","display_name":"Bogdan Ionescu","orcid":"https://orcid.org/0000-0003-4112-5769"},"institutions":[{"id":"https://openalex.org/I61641377","display_name":"Universitatea Na\u021bional\u0103 de \u0218tiin\u021b\u0103 \u0219i Tehnologie Politehnica Bucure\u0219ti","ror":"https://ror.org/0558j5q12","country_code":"RO","type":"education","lineage":["https://openalex.org/I61641377"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Bogdan Ionescu","raw_affiliation_strings":["Politehnica University of Bucharest, Bucharest, Romania"],"affiliations":[{"raw_affiliation_string":"Politehnica University of Bucharest, Bucharest, Romania","institution_ids":["https://openalex.org/I61641377"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5075315087"],"corresponding_institution_ids":["https://openalex.org/I61641377"],"apc_list":null,"apc_paid":null,"fwci":0.403,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.58386448,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"69","last_page":"77"},"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":0.9998000264167786,"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":0.9998000264167786,"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":0.9987000226974487,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9962000250816345,"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/computer-science","display_name":"Computer science","score":0.8294129371643066},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7515547275543213},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6844508647918701},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.6650813817977905},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6317398548126221},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6200510859489441},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5958926677703857},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45396173000335693},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4314611256122589},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.38250765204429626},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.14827284216880798}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8294129371643066},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7515547275543213},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6844508647918701},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.6650813817977905},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6317398548126221},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6200510859489441},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5958926677703857},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45396173000335693},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4314611256122589},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.38250765204429626},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.14827284216880798},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3512732.3533581","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3512732.3533581","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 1st International Workshop on Multimedia AI against Disinformation","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2966661","https://openalex.org/W2097117768","https://openalex.org/W2108598243","https://openalex.org/W2194775991","https://openalex.org/W2486034530","https://openalex.org/W2531409750","https://openalex.org/W2786289897","https://openalex.org/W2807126412","https://openalex.org/W2911424785","https://openalex.org/W2945262873","https://openalex.org/W2963073614","https://openalex.org/W2963524571","https://openalex.org/W2963616706","https://openalex.org/W2982058372","https://openalex.org/W3033543015","https://openalex.org/W3034713808","https://openalex.org/W3035063907","https://openalex.org/W3133531029","https://openalex.org/W3174508664","https://openalex.org/W4210699789"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W4377865163","https://openalex.org/W3193857078"],"abstract_inverted_index":{"Information":[0],"is":[1,16,36,67,96,167],"everywhere,":[2],"and":[3,38,69,106,153,177],"sometimes":[4,76],"we":[5,11,86],"have":[6],"no":[7,65],"idea":[8],"if":[9],"what":[10],"read,":[12],"watch":[13],"or":[14,19,30],"listen":[15],"accurate,":[17],"real":[18],"authentic.":[20],"This":[21],"paper":[22],"focuses":[23],"on":[24,88,170],"detecting":[25,52],"deep":[26,92,162],"learning":[27,93],"generated":[28],"videos,":[29],"deepfakes":[31],"-":[32],"a":[33,89,147,158],"phenomenon":[34],"which":[35],"more":[37,39],"present":[40],"in":[41,110,131],"today's":[42],"society.":[43],"While":[44],"there":[45,54],"are":[46,55,157],"some":[47],"very":[48,148,180],"good":[49],"methods":[50,94],"of":[51,91,134,151],"deepfakes,":[53],"two":[56,171],"key":[57],"elements":[58],"that":[59,95],"should":[60],"always":[61],"be":[62,129,140],"considered,":[63],"i.e.,":[64],"method":[66],"perfect":[68],"deepfake":[70,135],"generation":[71],"techniques":[72],"continue":[73],"to":[74,142],"evolve,":[75],"even":[77],"faster":[78],"than":[79],"detection":[80],"methods.":[81],"In":[82],"our":[83],"proposed":[84],"architectures,":[85],"focus":[87],"family":[90],"new,":[97],"has":[98,107],"several":[99],"advantages":[100],"over":[101,161],"traditional":[102],"Convolutional":[103],"Neural":[104],"Networks":[105,156],"been":[108],"underutilized":[109],"the":[111,117,132],"fight":[112],"against":[113],"fake":[114],"information,":[115],"namely":[116,175],"Capsule":[118,125,155],"Networks.":[119],"We":[120],"show":[121],"that:":[122],"(i)":[123],"state-of-the-art":[124],"Network":[126],"architectures":[127],"can":[128,139],"improved":[130],"context":[133],"detection,":[136],"(ii)":[137],"they":[138],"used":[141],"obtain":[143],"accurate":[144],"results":[145],"using":[146],"small":[149],"number":[150],"parameters,":[152],"(iii)":[154],"viable":[159],"option":[160],"convolutional":[163],"models.":[164],"Experimental":[165],"validation":[166],"carried":[168],"out":[169],"publicly":[172],"available":[173],"datasets,":[174],"FaceForensics++":[176],"CelebDF,":[178],"showing":[179],"promising":[181],"results.":[182]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}