{"id":"https://openalex.org/W4372338303","doi":"https://doi.org/10.1109/icassp49357.2023.10094654","title":"Frequency-Aware Attentional Feature Fusion for Deepfake Detection","display_name":"Frequency-Aware Attentional Feature Fusion for Deepfake Detection","publication_year":2023,"publication_date":"2023-05-05","ids":{"openalex":"https://openalex.org/W4372338303","doi":"https://doi.org/10.1109/icassp49357.2023.10094654"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49357.2023.10094654","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49357.2023.10094654","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5078634223","display_name":"Cheng Tian","orcid":"https://orcid.org/0000-0001-9671-1402"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Cheng Tian","raw_affiliation_strings":["Xiamen University,Department of Artificial Intelligence,Xiamen,China","Department of Artificial Intelligence, Xiamen University, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"Xiamen University,Department of Artificial Intelligence,Xiamen,China","institution_ids":["https://openalex.org/I191208505"]},{"raw_affiliation_string":"Department of Artificial Intelligence, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072443458","display_name":"Zhiming Luo","orcid":"https://orcid.org/0000-0002-3411-9582"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiming Luo","raw_affiliation_strings":["Xiamen University,Department of Artificial Intelligence,Xiamen,China","Department of Artificial Intelligence, Xiamen University, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"Xiamen University,Department of Artificial Intelligence,Xiamen,China","institution_ids":["https://openalex.org/I191208505"]},{"raw_affiliation_string":"Department of Artificial Intelligence, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061219220","display_name":"Guimin Shi","orcid":"https://orcid.org/0000-0002-3853-2972"},"institutions":[{"id":"https://openalex.org/I98834328","display_name":"Wuyi University","ror":"https://ror.org/059djzq42","country_code":"CN","type":"education","lineage":["https://openalex.org/I98834328"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guimin Shi","raw_affiliation_strings":["Wuyi University,Fujian Key Laboratory of Big Data Application and Intellectualization for Tea Industry,Wuyishan,China","Fujian Key Laboratory of Big Data Application and Intellectualization for Tea Industry, Wuyi University, Wuyishan, China"],"affiliations":[{"raw_affiliation_string":"Wuyi University,Fujian Key Laboratory of Big Data Application and Intellectualization for Tea Industry,Wuyishan,China","institution_ids":["https://openalex.org/I98834328"]},{"raw_affiliation_string":"Fujian Key Laboratory of Big Data Application and Intellectualization for Tea Industry, Wuyi University, Wuyishan, China","institution_ids":["https://openalex.org/I98834328"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081767617","display_name":"Shaozi Li","orcid":"https://orcid.org/0000-0001-5403-9945"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaozi Li","raw_affiliation_strings":["Xiamen University,Department of Artificial Intelligence,Xiamen,China","Department of Artificial Intelligence, Xiamen University, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"Xiamen University,Department of Artificial Intelligence,Xiamen,China","institution_ids":["https://openalex.org/I191208505"]},{"raw_affiliation_string":"Department of Artificial Intelligence, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5078634223"],"corresponding_institution_ids":["https://openalex.org/I191208505"],"apc_list":null,"apc_paid":null,"fwci":3.1976,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.93568654,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9994000196456909,"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":0.9991999864578247,"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/overfitting","display_name":"Overfitting","score":0.8611974716186523},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8266040086746216},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.7279735803604126},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6896588206291199},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6197367310523987},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5814397931098938},{"id":"https://openalex.org/keywords/closed-captioning","display_name":"Closed captioning","score":0.45147955417633057},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44277673959732056},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.426904559135437},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32463234663009644},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.22810223698616028},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.12909534573554993}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8611974716186523},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8266040086746216},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.7279735803604126},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6896588206291199},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6197367310523987},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5814397931098938},{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.45147955417633057},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44277673959732056},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.426904559135437},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32463234663009644},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.22810223698616028},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.12909534573554993},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49357.2023.10094654","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49357.2023.10094654","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"},{"score":0.44999998807907104,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321878","display_name":"Natural Science Foundation of Fujian Province","ror":null},{"id":"https://openalex.org/F4320324310","display_name":"Wuyi University","ror":"https://ror.org/059djzq42"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1665214252","https://openalex.org/W1710476689","https://openalex.org/W2341528187","https://openalex.org/W2531409750","https://openalex.org/W2600144439","https://openalex.org/W2618530766","https://openalex.org/W2891145043","https://openalex.org/W2898877033","https://openalex.org/W2909336075","https://openalex.org/W2951326654","https://openalex.org/W2982058372","https://openalex.org/W2998508940","https://openalex.org/W3005680577","https://openalex.org/W3012033723","https://openalex.org/W3033711348","https://openalex.org/W3034196597","https://openalex.org/W3034431451","https://openalex.org/W3034577585","https://openalex.org/W3034713808","https://openalex.org/W3035063907","https://openalex.org/W3035575271","https://openalex.org/W3094728142","https://openalex.org/W3101998545","https://openalex.org/W3108281670","https://openalex.org/W3108854358","https://openalex.org/W3158353280","https://openalex.org/W3166490340","https://openalex.org/W3174508664","https://openalex.org/W3174814557","https://openalex.org/W3176241004","https://openalex.org/W3200129610","https://openalex.org/W3203673582","https://openalex.org/W4224918448","https://openalex.org/W4287758545","https://openalex.org/W4292793883","https://openalex.org/W4297779039","https://openalex.org/W6637242042","https://openalex.org/W6727654133","https://openalex.org/W6755310813","https://openalex.org/W6756046522","https://openalex.org/W6774314701","https://openalex.org/W6775642233","https://openalex.org/W6784810453"],"related_works":["https://openalex.org/W4210416330","https://openalex.org/W1574414179","https://openalex.org/W4362597605","https://openalex.org/W3088136942","https://openalex.org/W2949362007","https://openalex.org/W2775506363","https://openalex.org/W4290852288","https://openalex.org/W3009056573","https://openalex.org/W4388893791","https://openalex.org/W4283207562"],"abstract_inverted_index":{"Various":[0],"face":[1],"manipulation":[2],"techniques":[3],"develop":[4],"rapidly":[5],"and":[6,59,72,84,124],"can":[7],"easily":[8],"generate":[9],"high-quality":[10],"fake":[11],"images":[12],"or":[13],"videos,":[14],"posing":[15],"significant":[16,28],"ethical":[17],"concerns":[18],"when":[19],"used":[20],"for":[21,53],"malicious":[22],"purposes.":[23],"Although":[24],"recent":[25],"works":[26],"achieve":[27],"performance":[29,121],"in":[30,122],"deepfake":[31,54],"detection,":[32],"they":[33],"still":[34],"suffer":[35],"from":[36,56],"overfitting":[37],"issues.":[38],"To":[39],"deal":[40],"with":[41],"this":[42],"problem,":[43],"we":[44,62,88],"propose":[45],"a":[46,65,90,102],"novel":[47],"framework":[48],"to":[49,69,75,95,109],"aggregate":[50],"diverse":[51],"information":[52,99],"detection":[55],"both":[57],"RGB":[58],"frequency.":[60],"Specially,":[61],"first":[63],"introduce":[64],"channel":[66],"attention":[67,104],"module":[68,94,105],"assemble":[70],"local":[71,82],"global":[73,85],"contexts":[74],"overcome":[76],"the":[77,97],"potential":[78],"semantic":[79],"inconsistency":[80],"on":[81],"artifacts":[83],"features.":[86],"Then":[87],"design":[89],"spatial-frequency":[91],"feature":[92,111],"fusion":[93],"fuse":[96],"RGB-frequency":[98],"comprehensively.":[100],"Moreover,":[101],"variant":[103],"is":[106],"further":[107],"proposed":[108],"improve":[110],"discrimination.":[112],"Extensive":[113],"experiments":[114],"demonstrate":[115],"that":[116],"our":[117],"method":[118],"maintains":[119],"comparable":[120],"intra-dataset":[123],"cross-dataset":[125],"evaluation.":[126]},"counts_by_year":[{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}