{"id":"https://openalex.org/W7125393327","doi":"https://doi.org/10.1109/tpami.2026.3656742","title":"Active Adversarial Noise Suppression for Image Forgery Localization","display_name":"Active Adversarial Noise Suppression for Image Forgery Localization","publication_year":2026,"publication_date":"2026-01-21","ids":{"openalex":"https://openalex.org/W7125393327","doi":"https://doi.org/10.1109/tpami.2026.3656742","pmid":"https://pubmed.ncbi.nlm.nih.gov/41564076"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2026.3656742","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2026.3656742","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5102852210","display_name":"R. C. Peng","orcid":"https://orcid.org/0009-0005-1707-8941"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rongxuan Peng","raw_affiliation_strings":["Shenzhen Key Laboratory of Media Security, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0007-3739-652X","affiliations":[{"raw_affiliation_string":"Shenzhen Key Laboratory of Media Security, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023503629","display_name":"Shunquan Tan","orcid":"https://orcid.org/0000-0002-7457-3691"},"institutions":[{"id":"https://openalex.org/I4388482657","display_name":"Shenzhen MSU-BIT University","ror":"https://ror.org/02q963474","country_code":null,"type":"education","lineage":["https://openalex.org/I4388482657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shunquan Tan","raw_affiliation_strings":["Guangdong Laboratory of Machine Perception and Intelligent Computing, Faculty of Engineering, Shenzhen MSU-BIT University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-7457-3691","affiliations":[{"raw_affiliation_string":"Guangdong Laboratory of Machine Perception and Intelligent Computing, Faculty of Engineering, Shenzhen MSU-BIT University, Shenzhen, China","institution_ids":["https://openalex.org/I4388482657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043791595","display_name":"Xianbo Mo","orcid":"https://orcid.org/0000-0001-9198-5041"},"institutions":[{"id":"https://openalex.org/I4388482657","display_name":"Shenzhen MSU-BIT University","ror":"https://ror.org/02q963474","country_code":null,"type":"education","lineage":["https://openalex.org/I4388482657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianbo Mo","raw_affiliation_strings":["Guangdong Laboratory of Machine Perception and Intelligent Computing, Faculty of Engineering, Shenzhen MSU-BIT University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong Laboratory of Machine Perception and Intelligent Computing, Faculty of Engineering, Shenzhen MSU-BIT University, Shenzhen, China","institution_ids":["https://openalex.org/I4388482657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123609688","display_name":"Alex C Kot","orcid":null},"institutions":[{"id":"https://openalex.org/I4388482657","display_name":"Shenzhen MSU-BIT University","ror":"https://ror.org/02q963474","country_code":null,"type":"education","lineage":["https://openalex.org/I4388482657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Alex C. Kot","raw_affiliation_strings":["Guangdong Laboratory of Machine Perception and Intelligent Computing, Faculty of Engineering, Shenzhen MSU-BIT University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-6262-8125","affiliations":[{"raw_affiliation_string":"Guangdong Laboratory of Machine Perception and Intelligent Computing, Faculty of Engineering, Shenzhen MSU-BIT University, Shenzhen, China","institution_ids":["https://openalex.org/I4388482657"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082818712","display_name":"JiWu HUANG","orcid":null},"institutions":[{"id":"https://openalex.org/I4388482657","display_name":"Shenzhen MSU-BIT University","ror":"https://ror.org/02q963474","country_code":null,"type":"education","lineage":["https://openalex.org/I4388482657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiwu Huang","raw_affiliation_strings":["Guangdong Laboratory of Machine Perception and Intelligent Computing, Faculty of Engineering, Shenzhen MSU-BIT University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-7625-5689","affiliations":[{"raw_affiliation_string":"Guangdong Laboratory of Machine Perception and Intelligent Computing, Faculty of Engineering, Shenzhen MSU-BIT University, Shenzhen, China","institution_ids":["https://openalex.org/I4388482657"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08371682,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"48","issue":"6","first_page":"6437","last_page":"6451"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.8478999733924866,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.8478999733924866,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.06759999692440033,"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":0.04540000110864639,"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/adversarial-system","display_name":"Adversarial system","score":0.9521999955177307},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.544700026512146},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4708999991416931},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.3935000002384186},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37880000472068787},{"id":"https://openalex.org/keywords/perturbation","display_name":"Perturbation (astronomy)","score":0.36390000581741333},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.3418999910354614},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.33809998631477356}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.9521999955177307},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.694599986076355},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6931999921798706},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.544700026512146},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5350000262260437},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4708999991416931},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.3935000002384186},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37880000472068787},{"id":"https://openalex.org/C177918212","wikidata":"https://www.wikidata.org/wiki/Q803623","display_name":"Perturbation (astronomy)","level":2,"score":0.36390000581741333},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.3418999910354614},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.33809998631477356},{"id":"https://openalex.org/C2780909371","wikidata":"https://www.wikidata.org/wiki/Q4801092","display_name":"Artificial noise","level":4,"score":0.3212999999523163},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.3059999942779541},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.2822999954223633},{"id":"https://openalex.org/C2983327147","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Image denoising","level":3,"score":0.28139999508857727},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.27810001373291016},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.2750999927520752},{"id":"https://openalex.org/C35772409","wikidata":"https://www.wikidata.org/wiki/Q1323086","display_name":"Image noise","level":3,"score":0.2703000009059906}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2026.3656742","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2026.3656742","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:41564076","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41564076","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7139384746551514,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G3775595010","display_name":null,"funder_award_id":"62272314","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7759657176","display_name":null,"funder_award_id":"62502314","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320320696","display_name":"Agency for Science, Technology and Research","ror":"https://ror.org/036wvzt09"},{"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":42,"referenced_works":["https://openalex.org/W1849277567","https://openalex.org/W1901129140","https://openalex.org/W2009130368","https://openalex.org/W2104116677","https://openalex.org/W2117539524","https://openalex.org/W2169439181","https://openalex.org/W2194775991","https://openalex.org/W2604505099","https://openalex.org/W2774644650","https://openalex.org/W2808402081","https://openalex.org/W2888493720","https://openalex.org/W2895129173","https://openalex.org/W2902355450","https://openalex.org/W2962914239","https://openalex.org/W2963447079","https://openalex.org/W2963542245","https://openalex.org/W2963857521","https://openalex.org/W3005588871","https://openalex.org/W3027377338","https://openalex.org/W3034779438","https://openalex.org/W3047891567","https://openalex.org/W3107235539","https://openalex.org/W3118025593","https://openalex.org/W3136675246","https://openalex.org/W3140970613","https://openalex.org/W3197106219","https://openalex.org/W3201680028","https://openalex.org/W3208354318","https://openalex.org/W3208634274","https://openalex.org/W4206589716","https://openalex.org/W4220829059","https://openalex.org/W4225554547","https://openalex.org/W4293846201","https://openalex.org/W4306966821","https://openalex.org/W4362468242","https://openalex.org/W4386076093","https://openalex.org/W4388858740","https://openalex.org/W4393170609","https://openalex.org/W4396214365","https://openalex.org/W4400905911","https://openalex.org/W4409364004","https://openalex.org/W7133229388"],"related_works":[],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2,194],"deep":[3],"learning":[4],"have":[5],"significantly":[6,158],"propelled":[7],"the":[8,55,97,107,128,160,177,188],"development":[9],"of":[10,58,191],"image":[11,195],"forgery":[12,141,161,196],"localization.":[13],"However,":[14],"existing":[15],"models":[16],"remain":[17],"highly":[18],"vulnerable":[19],"to":[20,26,53,144,173],"adversarial":[21,59,68,135,166,192],"attacks:":[22],"imperceptible":[23],"noise":[24],"added":[25],"forged":[27,71,138,175],"images":[28,72],"can":[29],"severely":[30],"mislead":[31],"these":[32,102],"models.":[33],"In":[34],"this":[35,39,78,186],"paper,":[36],"we":[37,80,110],"address":[38],"challenge":[40],"with":[41],"an":[42],"Adversarial":[43],"Noise":[44],"Suppression":[45],"Module":[46],"(ANSM)":[47],"that":[48,63,127,155],"generates":[49],"a":[50,87,112,122],"defensive":[51,108,129],"perturbation":[52,130],"suppress":[54],"attack":[56,152],"effect":[57],"noise.":[60],"We":[61],"observe":[62],"forgery-relevant":[64],"features":[65],"extracted":[66],"from":[67],"and":[69,136],"original":[70,137,146,174],"exhibit":[73],"distinct":[74],"distributions.":[75],"To":[76,104,182],"bridge":[77],"gap,":[79],"introduce":[81],"Forgery-relevant":[82],"Features":[83],"Alignment":[84],"(FFA)":[85],"as":[86],"first-stage":[88],"training":[89,114],"strategy,":[90,115],"which":[91,120],"reduces":[92],"distributional":[93],"discrepancies":[94],"by":[95],"minimizing":[96],"channel-wise":[98],"Kullback-Leibler":[99],"divergence":[100],"between":[101],"features.":[103],"further":[105],"refine":[106],"perturbation,":[109],"design":[111],"second-stage":[113],"termed":[116],"Mask-guided":[117],"Refinement":[118],"(MgR),":[119],"incorporates":[121],"dual-mask":[123],"constraint.":[124],"MgR":[125],"ensures":[126],"remains":[131,179],"effective":[132],"for":[133],"both":[134],"images,":[139,176],"recovering":[140],"localization":[142,162,197],"accuracy":[143],"their":[145],"level.":[147],"Extensive":[148],"experiments":[149],"across":[150],"various":[151],"algorithms":[153],"demonstrate":[154],"our":[156,183],"method":[157],"restores":[159],"model's":[163],"performance":[164,178],"on":[165],"images.":[167],"Notably,":[168],"when":[169],"ANSM":[170],"is":[171,187],"applied":[172],"nearly":[180],"unaffected.":[181],"best":[184],"knowledge,":[185],"first":[189],"report":[190],"defense":[193],"tasks.":[198]},"counts_by_year":[],"updated_date":"2026-05-09T06:09:20.037420","created_date":"2026-01-23T00:00:00"}