{"id":"https://openalex.org/W4405304221","doi":"https://doi.org/10.1109/besc64747.2024.10780603","title":"Generative Forgery Image Detection Based on Diffusion Reconstruction Loss and Frequency Domain Feature","display_name":"Generative Forgery Image Detection Based on Diffusion Reconstruction Loss and Frequency Domain Feature","publication_year":2024,"publication_date":"2024-08-16","ids":{"openalex":"https://openalex.org/W4405304221","doi":"https://doi.org/10.1109/besc64747.2024.10780603"},"language":"en","primary_location":{"id":"doi:10.1109/besc64747.2024.10780603","is_oa":false,"landing_page_url":"https://doi.org/10.1109/besc64747.2024.10780603","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 11th International Conference on Behavioural and Social Computing (BESC)","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/A5034377898","display_name":"Xinyang Hu","orcid":"https://orcid.org/0000-0002-8861-2567"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xinyang Hu","raw_affiliation_strings":["School of Computer Science, Beijing University of Posts and Telecommunications,Beijing,China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075117055","display_name":"E Haihong","orcid":"https://orcid.org/0000-0003-2087-586X"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haihong E","raw_affiliation_strings":["School of Computer Science, Beijing University of Posts and Telecommunications,Beijing,China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100405324","display_name":"Jianhua Liu","orcid":"https://orcid.org/0009-0006-4821-3189"},"institutions":[{"id":"https://openalex.org/I4210088738","display_name":"Wanfang Data (China)","ror":"https://ror.org/00502tg50","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210088738","https://openalex.org/I4210120069","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianhua Liu","raw_affiliation_strings":["Beijing Wanfang Data Co., Ltd.,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beijing Wanfang Data Co., Ltd.,Beijing,China","institution_ids":["https://openalex.org/I4210088738"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008262752","display_name":"Tianyi Hu","orcid":"https://orcid.org/0000-0002-2231-8170"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianyi Hu","raw_affiliation_strings":["School of Computer Science, Beijing University of Posts and Telecommunications,Beijing,China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102276147","display_name":"Xiaodong Qiao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210088738","display_name":"Wanfang Data (China)","ror":"https://ror.org/00502tg50","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210088738","https://openalex.org/I4210120069","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaodong Qiao","raw_affiliation_strings":["Beijing Wanfang Data Co., Ltd.,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beijing Wanfang Data Co., Ltd.,Beijing,China","institution_ids":["https://openalex.org/I4210088738"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101041184","display_name":"Junpeng Ding","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junpeng Ding","raw_affiliation_strings":["School of Computer Science, Beijing University of Posts and Telecommunications,Beijing,China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114549866","display_name":"Jiayu Huang","orcid":"https://orcid.org/0009-0004-7623-9533"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiayu Huang","raw_affiliation_strings":["School of Computer Science, Beijing University of Posts and Telecommunications,Beijing,China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5034377898"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.2518,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.56668216,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9837999939918518,"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":0.9837999939918518,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9513000249862671,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7076050043106079},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6971665620803833},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6674180030822754},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.6514553427696228},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5528994798660278},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5424429178237915},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5393874645233154},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5120082497596741},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.46700701117515564},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.4388979375362396},{"id":"https://openalex.org/keywords/feature-detection","display_name":"Feature detection (computer vision)","score":0.4176492989063263},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.4131411612033844},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.40058860182762146},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.20228248834609985},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14533519744873047}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7076050043106079},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6971665620803833},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6674180030822754},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.6514553427696228},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5528994798660278},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5424429178237915},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5393874645233154},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5120082497596741},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.46700701117515564},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4388979375362396},{"id":"https://openalex.org/C126422989","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature detection (computer vision)","level":4,"score":0.4176492989063263},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.4131411612033844},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.40058860182762146},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.20228248834609985},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14533519744873047},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/besc64747.2024.10780603","is_oa":false,"landing_page_url":"https://doi.org/10.1109/besc64747.2024.10780603","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 11th International Conference on Behavioural and Social Computing (BESC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5669621993","display_name":null,"funder_award_id":"62176026","funder_id":"https://openalex.org/F4320333688","funder_display_name":"National Outstanding Youth Science Fund Project of National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320333688","display_name":"National Outstanding Youth Science Fund Project of National Natural Science Foundation of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W3012472557","https://openalex.org/W3034795015","https://openalex.org/W3124962741","https://openalex.org/W4308234128","https://openalex.org/W4385567578","https://openalex.org/W4386071953","https://openalex.org/W4386075954","https://openalex.org/W4390189958","https://openalex.org/W6775642233","https://openalex.org/W6783713337","https://openalex.org/W6857500224"],"related_works":["https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W4391584540","https://openalex.org/W4380551139","https://openalex.org/W4317695495","https://openalex.org/W4395044357","https://openalex.org/W4287117424","https://openalex.org/W4387506531","https://openalex.org/W2087346071","https://openalex.org/W2967848559"],"abstract_inverted_index":{"Since":[0],"the":[1,20,27,41,59,66,80,103,181,186],"advent":[2],"of":[3,22,29,44,61,68,180,190],"generative":[4,118,149,213],"models":[5],"such":[6],"as":[7],"Generative":[8],"Adversarial":[9],"Networks":[10],"(GANs),":[11],"image":[12,24,63,83,176],"generation":[13,60,84,104],"techniques":[14,31,74],"have":[15,94],"made":[16],"significant":[17],"progress":[18],"in":[19,37,47,65,205],"field":[21,67],"digital":[23],"processing.":[25],"However,":[26],"development":[28],"these":[30],"has":[32],"also":[33],"brought":[34],"about":[35],"challenges":[36],"research":[38,48,55,69,90,155],"integrity,":[39],"especially":[40,86],"growing":[42],"problem":[43],"forged":[45,62,113,150,208],"images":[46,92,114,151,168,209],"papers.":[49],"Currently,":[50],"there":[51],"are":[52,75,99],"no":[53],"mature":[54],"results":[56],"related":[57],"to":[58,77,79,109,125,145,161,166,184],"detection":[64,73,135],"integrity":[70],"detection.":[71,191],"Existing":[72,106],"difficult":[76],"adapt":[78],"rapidly":[81],"evolving":[82],"models,":[85,119],"when":[87],"dealing":[88],"with":[89,175],"paper":[91],"that":[93,137],"a":[95,122,133,159,195],"single":[96],"structure":[97],"and":[98,142,147,172,188],"quickly":[100],"learned":[101],"by":[102,116,211],"models.":[105,214],"methods":[107],"fail":[108],"effectively":[110,206],"identify":[111,146],"high-quality":[112],"produced":[115,210],"advanced":[117],"which":[120],"poses":[121],"severe":[123],"threat":[124],"scientific":[126,154],"integrity.":[127],"In":[128],"this":[129],"study,":[130],"we":[131],"propose":[132],"new":[134],"method":[136,201],"combines":[138],"diffusion":[139,182],"reconfiguration":[140],"loss":[141],"frequency-domain":[143,163,170],"features":[144,179],"differentiate":[148],"from":[152],"fundamental":[153],"images.":[156],"We":[157],"developed":[158],"technique":[160],"detect":[162],"artifacts":[164],"specific":[165],"generated":[167],"using":[169],"analysis":[171],"combined":[173],"it":[174],"reconstruction":[177],"error":[178],"model":[183],"enhance":[185],"accuracy":[187],"robustness":[189],"Through":[192],"testing":[193],"on":[194],"newly":[196],"constructed":[197],"public":[198],"dataset,":[199],"our":[200],"shows":[202],"superior":[203],"performance":[204],"identifying":[207],"multiple":[212]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-25T14:56:36.534964","created_date":"2025-10-10T00:00:00"}