{"id":"https://openalex.org/W4402897183","doi":"https://doi.org/10.1109/icsipa62061.2024.10687088","title":"Attention-Guided Supervised Contrastive Learning for Deepfake Detection","display_name":"Attention-Guided Supervised Contrastive Learning for Deepfake Detection","publication_year":2024,"publication_date":"2024-09-03","ids":{"openalex":"https://openalex.org/W4402897183","doi":"https://doi.org/10.1109/icsipa62061.2024.10687088"},"language":"en","primary_location":{"id":"doi:10.1109/icsipa62061.2024.10687088","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsipa62061.2024.10687088","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 8th International Conference on Signal and Image Processing Applications (ICSIPA)","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/A5078381823","display_name":"Saima Waseem","orcid":"https://orcid.org/0000-0001-7704-7059"},"institutions":[{"id":"https://openalex.org/I4576418","display_name":"University of Technology Malaysia","ror":"https://ror.org/026w31v75","country_code":"MY","type":"education","lineage":["https://openalex.org/I4576418"]}],"countries":["MY"],"is_corresponding":true,"raw_author_name":"Saima Waseem","raw_affiliation_strings":["Universiti Teknologi Malaysia,Faculty of Electrical Engineering,Johor,Malaysia"],"affiliations":[{"raw_affiliation_string":"Universiti Teknologi Malaysia,Faculty of Electrical Engineering,Johor,Malaysia","institution_ids":["https://openalex.org/I4576418"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113404359","display_name":"Syed Abdul Rahman Bin Syed Abu Bakar","orcid":null},"institutions":[{"id":"https://openalex.org/I4576418","display_name":"University of Technology Malaysia","ror":"https://ror.org/026w31v75","country_code":"MY","type":"education","lineage":["https://openalex.org/I4576418"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Syed Abdul Rahman Bin Syed Abu Bakar","raw_affiliation_strings":["Universiti Teknologi Malaysia,Faculty of Electrical Engineering,Johor,Malaysia"],"affiliations":[{"raw_affiliation_string":"Universiti Teknologi Malaysia,Faculty of Electrical Engineering,Johor,Malaysia","institution_ids":["https://openalex.org/I4576418"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101993937","display_name":"Bilal Ashfaq Ahmed","orcid":"https://orcid.org/0000-0002-3981-7558"},"institutions":[{"id":"https://openalex.org/I4576418","display_name":"University of Technology Malaysia","ror":"https://ror.org/026w31v75","country_code":"MY","type":"education","lineage":["https://openalex.org/I4576418"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Bilal Ashfaq Ahmed","raw_affiliation_strings":["Universiti Teknologi Malaysia,Faculty of Computing,Johor,Malaysia"],"affiliations":[{"raw_affiliation_string":"Universiti Teknologi Malaysia,Faculty of Computing,Johor,Malaysia","institution_ids":["https://openalex.org/I4576418"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5078381823"],"corresponding_institution_ids":["https://openalex.org/I4576418"],"apc_list":null,"apc_paid":null,"fwci":0.7895,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.73444857,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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":0.9588000178337097,"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":0.9588000178337097,"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":0.9448000192642212,"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":0.7353432774543762},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5196186900138855},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5037075877189636},{"id":"https://openalex.org/keywords/statistical-learning","display_name":"Statistical learning","score":0.4135409891605377}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7353432774543762},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5196186900138855},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5037075877189636},{"id":"https://openalex.org/C2982736386","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Statistical learning","level":2,"score":0.4135409891605377}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icsipa62061.2024.10687088","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsipa62061.2024.10687088","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 8th International Conference on Signal and Image Processing Applications (ICSIPA)","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":35,"referenced_works":["https://openalex.org/W2138621090","https://openalex.org/W2891145043","https://openalex.org/W2909336075","https://openalex.org/W2911424785","https://openalex.org/W2913399670","https://openalex.org/W2963043696","https://openalex.org/W2963684180","https://openalex.org/W2982058372","https://openalex.org/W2997517962","https://openalex.org/W3034713808","https://openalex.org/W3094728142","https://openalex.org/W3154326567","https://openalex.org/W3164861235","https://openalex.org/W3173317327","https://openalex.org/W3174508664","https://openalex.org/W3183999072","https://openalex.org/W4200606280","https://openalex.org/W4205432403","https://openalex.org/W4220658233","https://openalex.org/W4220984393","https://openalex.org/W4252096362","https://openalex.org/W4289752563","https://openalex.org/W4323364877","https://openalex.org/W4385986617","https://openalex.org/W4387609212","https://openalex.org/W4390239642","https://openalex.org/W4391543938","https://openalex.org/W6751846511","https://openalex.org/W6756046522","https://openalex.org/W6762480454","https://openalex.org/W6762718338","https://openalex.org/W6769705151","https://openalex.org/W6769741248","https://openalex.org/W6776700526","https://openalex.org/W6797428907"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Recent":[0],"advancements":[1],"in":[2,64,80,107,175],"face":[3,19],"deepfake":[4,63,101,166,173,189],"detection":[5,21,174],"have":[6],"shown":[7],"impressive":[8],"results.":[9],"However,":[10],"prior":[11],"studies":[12],"typically":[13],"used":[14],"crossentropy":[15],"loss":[16,30],"to":[17,49,51,71,76,84,104,130,146],"approach":[18,99],"manipulation":[20],"as":[22,195],"a":[23,86,132,162],"classification":[24],"problem.":[25],"Approaches":[26],"based":[27],"on":[28,120,191],"cross-entropy":[29],"prioritize":[31,112],"category":[32],"distinctions":[33],"over":[34],"capturing":[35],"the":[36,46,62,78,81,108,127,144,170,181],"underlying":[37],"differences":[38,79,106],"between":[39,114,137],"real":[40],"and":[41,111,152,199],"fake":[42],"faces,":[43],"which":[44],"restricts":[45],"model's":[47],"capacity":[48],"generalize":[50],"unseen":[52,176],"datasets.":[53,177],"As":[54],"original":[55],"image":[56],"or":[57],"video":[58],"can":[59],"closely":[60],"resemble":[61],"terms":[65],"of":[66,165,172,183],"appearance,":[67],"making":[68],"it":[69],"challenging":[70],"distinguish":[72],"them,":[73],"we":[74,92],"propose":[75],"utilize":[77],"representation":[82,109,134],"space":[83,110],"develop":[85],"generalizable":[87],"detector.":[88],"In":[89],"this":[90],"paper,":[91],"present":[93],"an":[94,140],"attention-guided":[95,185],"supervised":[96,124,186],"contrastive":[97,125,187],"learning":[98,188],"for":[100,149],"detection,":[102],"aiming":[103],"leverage":[105],"disparities":[113],"classes":[115],"rather":[116],"than":[117],"focusing":[118],"solely":[119],"categories.":[121],"By":[122],"using":[123],"learning,":[126],"model":[128,145],"learns":[129,159],"create":[131],"discriminative":[133],"by":[135],"contrasting":[136],"classes,":[138],"while":[139],"attention":[141],"module":[142],"directs":[143],"relevant":[147],"features":[148,160],"each":[150],"class":[151],"filters":[153],"out":[154],"irrelevant":[155],"features.":[156],"This":[157],"method":[158],"from":[161],"wide":[163],"variety":[164],"images,":[167],"thus":[168],"improving":[169],"accuracy":[171],"Experimental":[178],"results":[179],"show":[180],"effectiveness":[182],"our":[184],"detector":[190],"benchmark":[192],"datasets":[193],"such":[194],"FF++,":[196],"Celeb-DF,":[197],"DFD":[198],"DFDC-P.":[200]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}