{"id":"https://openalex.org/W4319663742","doi":"https://doi.org/10.1109/lsp.2023.3243770","title":"New Finding and Unified Framework for Fake Image Detection","display_name":"New Finding and Unified Framework for Fake Image Detection","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4319663742","doi":"https://doi.org/10.1109/lsp.2023.3243770"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2023.3243770","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2023.3243770","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-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/A5040495514","display_name":"Xin Deng","orcid":"https://orcid.org/0000-0002-4708-6572"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Deng","raw_affiliation_strings":["School of Cyber Science and Technology, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4708-6572","affiliations":[{"raw_affiliation_string":"School of Cyber Science and Technology, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079046940","display_name":"Bihe Zhao","orcid":"https://orcid.org/0000-0001-8349-4533"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bihe Zhao","raw_affiliation_strings":["School of Cyber Science and Technology, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8349-4533","affiliations":[{"raw_affiliation_string":"School of Cyber Science and Technology, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083017828","display_name":"Zhenyu Guan","orcid":"https://orcid.org/0000-0002-3959-338X"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenyu Guan","raw_affiliation_strings":["School of Cyber Science and Technology, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3959-338X","affiliations":[{"raw_affiliation_string":"School of Cyber Science and Technology, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079385534","display_name":"Mai Xu","orcid":"https://orcid.org/0000-0002-0277-3301"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mai Xu","raw_affiliation_strings":["School of Electronic and Information Engineering, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0277-3301","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":1.2222,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.80931602,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"30","issue":null,"first_page":"90","last_page":"94"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9995999932289124,"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":0.9995999932289124,"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"}},{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9930999875068665,"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":0.761178731918335},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7053624391555786},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5586411356925964},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5480797290802002},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5117568969726562},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.49198290705680847},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4728429913520813},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4526611566543579},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.42586660385131836},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.4116489291191101},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.38330695033073425}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.761178731918335},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7053624391555786},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5586411356925964},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5480797290802002},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5117568969726562},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.49198290705680847},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4728429913520813},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4526611566543579},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.42586660385131836},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.4116489291191101},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.38330695033073425},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2023.3243770","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2023.3243770","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G6107143743","display_name":null,"funder_award_id":"62001016","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1834627138","https://openalex.org/W2056370875","https://openalex.org/W2062811295","https://openalex.org/W2097073572","https://openalex.org/W2187089797","https://openalex.org/W2289795235","https://openalex.org/W2301937176","https://openalex.org/W2549139847","https://openalex.org/W2891145043","https://openalex.org/W2909336075","https://openalex.org/W2914447220","https://openalex.org/W2962770929","https://openalex.org/W2962858109","https://openalex.org/W2963091558","https://openalex.org/W2963446712","https://openalex.org/W2963626105","https://openalex.org/W2963684180","https://openalex.org/W2963767194","https://openalex.org/W2982058372","https://openalex.org/W3034600949","https://openalex.org/W3034795015","https://openalex.org/W3035574324","https://openalex.org/W3036806226","https://openalex.org/W3094728142","https://openalex.org/W3158353280","https://openalex.org/W3174508664","https://openalex.org/W3174814557","https://openalex.org/W3176241004","https://openalex.org/W3183999072","https://openalex.org/W4295046718","https://openalex.org/W4295046748","https://openalex.org/W4312311597","https://openalex.org/W6745560452","https://openalex.org/W6758681311"],"related_works":["https://openalex.org/W2336272890","https://openalex.org/W4308999381","https://openalex.org/W3183843611","https://openalex.org/W4312238398","https://openalex.org/W3211418293","https://openalex.org/W4308999963","https://openalex.org/W2985118265","https://openalex.org/W3204852000","https://openalex.org/W2901758161","https://openalex.org/W4285815683"],"abstract_inverted_index":{"Recently,":[0],"fake":[1,27,39,61,84,94],"face":[2,146],"images":[3,40,62,95,126],"generated":[4,60,93],"by":[5,72,118],"generative":[6],"adversarial":[7],"network":[8],"(GAN)":[9],"have":[10],"been":[11],"widely":[12],"spread":[13],"in":[14],"social":[15,19],"networks,":[16],"raising":[17],"serious":[18],"concerns":[20],"and":[21],"security":[22],"risks.":[23],"To":[24],"identify":[25],"the":[26,29,38,43,58,68,110,114,125,128,138,153,174,180,188,191],"images,":[28,56,116],"top":[30],"priority":[31],"is":[32,156],"to":[33,90,108,123],"find":[34],"what":[35],"properties":[36],"make":[37],"different":[41],"from":[42,96,158],"real":[44,69,97],"images.":[45,70,98],"In":[46],"this":[47,73],"letter,":[48],"we":[49,75,100,160],"reveal":[50],"an":[51],"important":[52],"observation":[53],"about":[54],"real/fake":[55,115],"i.e.,":[57],"GAN":[59,92],"contain":[63],"stronger":[64],"non-local":[65,81,103,111,130],"self-similarity":[66],"than":[67],"Motivated":[71],"observation,":[74],"propose":[76],"a":[77,102,119],"simple":[78],"yet":[79],"effective":[80],"attention":[82],"based":[83],"image":[85],"detection":[86,148,168,181],"network,":[87],"namely":[88],"NAFID,":[89],"distinguish":[91,124],"Specifically,":[99],"develop":[101],"feature":[104],"extraction":[105],"(NFE)":[106],"module":[107,122,155,176],"extract":[109],"features":[112],"of":[113,140,183,190],"followed":[117],"multi-stage":[120],"classification":[121],"with":[127],"extracted":[129],"features.":[131],"Experimental":[132],"results":[133,171],"on":[134],"various":[135],"datasets":[136],"demonstrate":[137],"superiority":[139],"our":[141],"NAFID":[142],"over":[143],"state-of-the-art":[144],"(SOTA)":[145],"forgery":[147,167],"methods.":[149],"More":[150],"importantly,":[151],"since":[152],"NFE":[154,175],"independent":[157],"classification,":[159],"can":[161,177],"plug":[162],"it":[163],"into":[164],"any":[165],"other":[166,184],"models.":[169],"The":[170],"show":[172],"that":[173],"consistently":[178],"improve":[179],"accuracy":[182],"models,":[185],"which":[186],"verifies":[187],"universality":[189],"proposed":[192],"method.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
