{"id":"https://openalex.org/W4408352321","doi":"https://doi.org/10.1109/icassp49660.2025.10889149","title":"Knowledge-Guided Prompt Learning for Deepfake Facial Image Detection","display_name":"Knowledge-Guided Prompt Learning for Deepfake Facial Image Detection","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408352321","doi":"https://doi.org/10.1109/icassp49660.2025.10889149"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10889149","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10889149","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 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/A5101740092","display_name":"Hao Wang","orcid":"https://orcid.org/0000-0002-0013-7328"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Wang","raw_affiliation_strings":["Hangzhou Dianzi University,School of Cyberspace Security,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hangzhou Dianzi University,School of Cyberspace Security,Hangzhou,China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015874725","display_name":"Cheng Deng","orcid":"https://orcid.org/0000-0003-2620-3247"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Deng","raw_affiliation_strings":["Xidian University,School of Electronic Engineering,Xi’an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xidian University,School of Electronic Engineering,Xi’an,China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086944905","display_name":"Zhidong Zhao","orcid":"https://orcid.org/0009-0008-7945-8466"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhidong Zhao","raw_affiliation_strings":["Hangzhou Dianzi University,School of Cyberspace Security,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hangzhou Dianzi University,School of Cyberspace Security,Hangzhou,China","institution_ids":["https://openalex.org/I50760025"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.8699,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.84146354,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"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/T11448","display_name":"Face recognition and analysis","score":0.9627000093460083,"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/T11448","display_name":"Face recognition and analysis","score":0.9627000093460083,"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":0.793704628944397},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6229533553123474},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.579770565032959},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.48574429750442505},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3936902582645416},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3594934940338135}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.793704628944397},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6229533553123474},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.579770565032959},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48574429750442505},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3936902582645416},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3594934940338135}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49660.2025.10889149","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10889149","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2250384498","https://openalex.org/W2811414481","https://openalex.org/W2963857521","https://openalex.org/W2991318208","https://openalex.org/W3034577585","https://openalex.org/W3040168631","https://openalex.org/W3094728142","https://openalex.org/W3096831136","https://openalex.org/W3108281670","https://openalex.org/W3173126908","https://openalex.org/W3174508664","https://openalex.org/W3175734111","https://openalex.org/W3187526215","https://openalex.org/W4293146779","https://openalex.org/W4308234128","https://openalex.org/W4308237189","https://openalex.org/W4312310776","https://openalex.org/W4372338303","https://openalex.org/W4386071547","https://openalex.org/W4386071953","https://openalex.org/W4386590781","https://openalex.org/W4392904043","https://openalex.org/W4402716375","https://openalex.org/W4402753859","https://openalex.org/W4405208292","https://openalex.org/W6625168331","https://openalex.org/W6631190155","https://openalex.org/W6745560452","https://openalex.org/W6775642233","https://openalex.org/W6779823529","https://openalex.org/W6784333009","https://openalex.org/W6791353385","https://openalex.org/W6857629293","https://openalex.org/W6858057904"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407"],"abstract_inverted_index":{"Recent":[0],"generative":[1],"models":[2,103],"demonstrate":[3],"impressive":[4],"performance":[5,127],"on":[6,21,30,138],"synthesizing":[7],"photographic":[8],"images,":[9],"which":[10],"makes":[11],"humans":[12],"hardly":[13],"to":[14,53,107,120],"distinguish":[15],"them":[16],"from":[17,34,100],"pristine":[18],"ones,":[19],"especially":[20],"realistic-looking":[22],"synthetic":[23],"facial":[24,71,92],"images.":[25],"Previous":[26],"works":[27],"mostly":[28],"focus":[29],"mining":[31],"discriminative":[32],"artifacts":[33],"vast":[35],"amount":[36],"of":[37,46,111],"visual":[38],"data.":[39],"However,":[40],"they":[41],"usually":[42],"lack":[43],"the":[44,54,109,122,131],"exploration":[45],"prior":[47],"knowledge":[48,106],"and":[49,62,65,129],"rarely":[50],"pay":[51],"attention":[52],"domain":[55,123],"shift":[56],"between":[57],"training":[58],"categories":[59],"(e.g.,":[60,68],"natural":[61],"indoor":[63],"objects)":[64],"testing":[66],"ones":[67],"fine-grained":[69],"human":[70],"images),":[72],"resulting":[73],"in":[74,133],"unsatisfactory":[75],"detection":[76],"performance.":[77],"To":[78],"address":[79],"these":[80],"issues,":[81],"we":[82,96,115],"propose":[83],"a":[84],"novel":[85],"knowledge-guided":[86],"prompt":[87,118],"learning":[88],"method":[89],"for":[90],"deepfake":[91],"image":[93],"detection.":[94],"Specifically,":[95],"retrieve":[97],"forgery-related":[98],"prompts":[99],"large":[101],"language":[102],"as":[104],"expert":[105],"guide":[108],"optimization":[110],"learnable":[112],"prompts.":[113],"Besides,":[114],"elaborate":[116],"test-time":[117],"tuning":[119],"alleviate":[121],"shift,":[124],"achieving":[125],"significant":[126],"improvement":[128],"boosting":[130],"application":[132],"real-world":[134],"scenarios.":[135],"Extensive":[136],"experiments":[137],"DeepFakeFaceForensics":[139],"dataset":[140],"show":[141],"that":[142],"our":[143],"proposed":[144],"approach":[145],"notably":[146],"outperforms":[147],"state-of-the-art":[148],"methods.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}