{"id":"https://openalex.org/W4285304173","doi":"https://doi.org/10.1109/tcsvt.2022.3177238","title":"BDC-GAN: Bidirectional Conversion Between Computer-Generated and Natural Facial Images for Anti-Forensics","display_name":"BDC-GAN: Bidirectional Conversion Between Computer-Generated and Natural Facial Images for Anti-Forensics","publication_year":2022,"publication_date":"2022-05-23","ids":{"openalex":"https://openalex.org/W4285304173","doi":"https://doi.org/10.1109/tcsvt.2022.3177238"},"language":"en","primary_location":{"id":"doi:10.1109/tcsvt.2022.3177238","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2022.3177238","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"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 Transactions on Circuits and Systems for Video Technology","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/A5049120636","display_name":"Fei Peng","orcid":"https://orcid.org/0000-0001-8053-4587"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Peng","raw_affiliation_strings":["Institute of Artificial Intelligence and Blockchain, Guangzhou University, Guangzhou, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0001-8053-4587","affiliations":[{"raw_affiliation_string":"Institute of Artificial Intelligence and Blockchain, Guangzhou University, Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103206140","display_name":"Liping Yin","orcid":"https://orcid.org/0000-0002-3165-9794"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liping Yin","raw_affiliation_strings":["School of Computer Science and Electronic Engineering, Hunan University, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Electronic Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078874201","display_name":"Min Long","orcid":"https://orcid.org/0000-0002-1229-2317"},"institutions":[{"id":"https://openalex.org/I56934997","display_name":"Changsha University of Science and Technology","ror":"https://ror.org/03yph8055","country_code":"CN","type":"education","lineage":["https://openalex.org/I56934997"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Long","raw_affiliation_strings":["School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-1229-2317","affiliations":[{"raw_affiliation_string":"School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha, China","institution_ids":["https://openalex.org/I56934997"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.0307,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.87989137,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"32","issue":"10","first_page":"6657","last_page":"6670"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9987000226974487,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9894999861717224,"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":0.8197640180587769},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6659021377563477},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.596229076385498},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.5946521759033203},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.5846540331840515},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5139831900596619},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48778825998306274},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4655739963054657},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.30540192127227783}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8197640180587769},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6659021377563477},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.596229076385498},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.5946521759033203},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.5846540331840515},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5139831900596619},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48778825998306274},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4655739963054657},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.30540192127227783},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsvt.2022.3177238","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2022.3177238","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"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 Transactions on Circuits and Systems for Video Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6899999976158142,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G1843846948","display_name":"\u57fa\u4e8e\u6df1\u5ea6\u5b66\u4e60\u7684\u4eba\u8138\u878d\u5408\u53d6\u8bc1\u7814\u7a76","funder_award_id":"62072055","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5582328184","display_name":null,"funder_award_id":"U1936115","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8271725175","display_name":null,"funder_award_id":"92067104","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W305574147","https://openalex.org/W1686810756","https://openalex.org/W1834627138","https://openalex.org/W2009130368","https://openalex.org/W2040648696","https://openalex.org/W2051459466","https://openalex.org/W2069878189","https://openalex.org/W2095130919","https://openalex.org/W2099471712","https://openalex.org/W2111374353","https://openalex.org/W2124695272","https://openalex.org/W2151825689","https://openalex.org/W2274484468","https://openalex.org/W2416656465","https://openalex.org/W2509155366","https://openalex.org/W2535388113","https://openalex.org/W2554354039","https://openalex.org/W2593414223","https://openalex.org/W2603777577","https://openalex.org/W2755986598","https://openalex.org/W2767825479","https://openalex.org/W2772755592","https://openalex.org/W2786289897","https://openalex.org/W2794515184","https://openalex.org/W2797335731","https://openalex.org/W2799785652","https://openalex.org/W2852084320","https://openalex.org/W2883088976","https://openalex.org/W2914227139","https://openalex.org/W2962793481","https://openalex.org/W2963444790","https://openalex.org/W2963800363","https://openalex.org/W2963890275","https://openalex.org/W2964295764","https://openalex.org/W2984417234","https://openalex.org/W2994892543","https://openalex.org/W3007646528","https://openalex.org/W3035037798","https://openalex.org/W3082772348","https://openalex.org/W3101649689","https://openalex.org/W3166279462","https://openalex.org/W3166490340","https://openalex.org/W3199474181","https://openalex.org/W3204217431","https://openalex.org/W4244098250","https://openalex.org/W6637373629","https://openalex.org/W6638485062","https://openalex.org/W6735204497","https://openalex.org/W6759318644"],"related_works":["https://openalex.org/W4293202849","https://openalex.org/W1980965563","https://openalex.org/W1489300767","https://openalex.org/W4380714744","https://openalex.org/W2387995142","https://openalex.org/W4319453655","https://openalex.org/W2057775761","https://openalex.org/W2964074194","https://openalex.org/W4321441197","https://openalex.org/W4308217387"],"abstract_inverted_index":{"Aiming":[0],"at":[1],"degrading":[2],"the":[3,6,53,64,69,73,83,93,96,110,134,143,153,168,187,190,198,214,218],"capability":[4],"of":[5,42,46,68,95,217,220],"existing":[7,169,191,199],"forensic":[8,193,200],"methods":[9,175],"in":[10,37,109],"discriminating":[11],"computer":[12,221],"generated":[13,222],"and":[14,23,49,71,89,102,121,127,149,162,176,181,209,223],"natural":[15,24,224],"facial":[16,25,145,172,225],"images,":[17],"a":[18],"bidirectional":[19,135,177],"conversion":[20,136],"between":[21,137],"computer-generated":[22],"images":[26,140],"based":[27],"on":[28,189],"generative":[29],"adversarial":[30,207],"network":[31],"(BDC-GAN)":[32],"is":[33,44,77,87,184],"proposed":[34,154],"for":[35],"anti-forensics":[36],"this":[38],"paper.":[39],"The":[40,112],"generator":[41],"BDC-GAN":[43],"composed":[45],"noise":[47,54,67,122],"encoding":[48],"content":[50,84,94,119],"encoding.":[51,81],"In":[52,82],"encoding,":[55,85],"three":[56],"high-pass":[57],"filters":[58],"are":[59,107,124,129],"first":[60],"utilized":[61],"to":[62,79,91,132],"extract":[63],"sensor":[65],"pattern":[66],"image,":[70],"then":[72],"stacked":[74,99],"convolution":[75,100],"layer":[76,106],"combined":[78],"continue":[80],"VGG-19":[86],"truncated":[88],"fine-tuned":[90],"encode":[92],"image.":[97],"Some":[98],"layers":[101],"adaptive":[103,179],"instance":[104],"normalization":[105],"used":[108],"decoder.":[111],"discriminator":[113],"uses":[114],"multi-scale":[115],"image":[116,173],"discriminator.":[117],"Furthermore,":[118],"loss":[120,123],"well":[125],"designed,":[126],"hyperparameters":[128],"reasonably":[130],"set":[131],"accomplish":[133],"two":[138],"domain":[139,178],"meanwhile":[141],"retaining":[142],"original":[144],"contour.":[146],"Experimental":[147],"results":[148],"analysis":[150],"demonstrate":[151],"that":[152,197],"anti-forensic":[155,174],"method":[156],"can":[157,202],"achieve":[158],"better":[159],"visual":[160],"quality":[161],"stronger":[163],"deception":[164],"ability":[165],"compared":[166],"with":[167],"unidirectional":[170],"CG":[171],"methods,":[180],"its":[182],"effectiveness":[183],"verified":[185],"by":[186,205],"tests":[188],"9":[192],"methods.":[194],"It":[195],"reveals":[196],"techniques":[201],"be":[203],"bypassed":[204],"using":[206],"learning,":[208],"it":[210],"will":[211],"eventually":[212],"push":[213],"performance":[215],"improvement":[216],"discrimination":[219],"images.":[226]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
