{"id":"https://openalex.org/W7125828141","doi":"https://doi.org/10.1109/tifs.2026.3657841","title":"Adversarial Diffusion Model: Generating High-Quality and Undetectable Images From Scratch","display_name":"Adversarial Diffusion Model: Generating High-Quality and Undetectable Images From Scratch","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7125828141","doi":"https://doi.org/10.1109/tifs.2026.3657841"},"language":null,"primary_location":{"id":"doi:10.1109/tifs.2026.3657841","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2026.3657841","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"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 Information Forensics and Security","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/A5124013892","display_name":"Haoyue Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoyue Wang","raw_affiliation_strings":["College of Computer Science and Artificial Intelligence, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0009-0645-8729","affiliations":[{"raw_affiliation_string":"College of Computer Science and Artificial Intelligence, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124005580","display_name":"Sheng Li","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sheng Li","raw_affiliation_strings":["College of Computer Science and Artificial Intelligence, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-7589-9554","affiliations":[{"raw_affiliation_string":"College of Computer Science and Artificial Intelligence, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123909691","display_name":"Zhenxing Qian","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenxing Qian","raw_affiliation_strings":["College of Computer Science and Artificial Intelligence, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-1622-0561","affiliations":[{"raw_affiliation_string":"College of Computer Science and Artificial Intelligence, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124047435","display_name":"Xinpeng Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinpeng Zhang","raw_affiliation_strings":["College of Computer Science and Artificial Intelligence, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-0212-3501","affiliations":[{"raw_affiliation_string":"College of Computer Science and Artificial Intelligence, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":19.5563,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.97752148,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"21","issue":null,"first_page":"1725","last_page":"1736"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.8895999789237976,"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":0.8895999789237976,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.0722000002861023,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.012299999594688416,"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":0.9492999911308289},{"id":"https://openalex.org/keywords/scratch","display_name":"Scratch","score":0.5839999914169312},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.5673999786376953},{"id":"https://openalex.org/keywords/compensation","display_name":"Compensation (psychology)","score":0.4453999996185303},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.38830000162124634},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.38580000400543213},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.37119999527931213}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.9492999911308289},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8091999888420105},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5946000218391418},{"id":"https://openalex.org/C2781235140","wikidata":"https://www.wikidata.org/wiki/Q275131","display_name":"Scratch","level":2,"score":0.5839999914169312},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.5673999786376953},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.447299987077713},{"id":"https://openalex.org/C2780023022","wikidata":"https://www.wikidata.org/wiki/Q1338171","display_name":"Compensation (psychology)","level":2,"score":0.4453999996185303},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.38830000162124634},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.38580000400543213},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37619999051094055},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.37119999527931213},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.3334999978542328},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3176000118255615},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.313400000333786},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.2962000072002411},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2944999933242798},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.27489998936653137},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.2685999870300293},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.25920000672340393}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tifs.2026.3657841","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2026.3657841","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"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 Information Forensics and Security","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1961232708","display_name":null,"funder_award_id":"U22B2047","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5685869395","display_name":null,"funder_award_id":"62572125","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":40,"referenced_works":["https://openalex.org/W2108598243","https://openalex.org/W2194775991","https://openalex.org/W2962847335","https://openalex.org/W3034577585","https://openalex.org/W3034864980","https://openalex.org/W3035574324","https://openalex.org/W3108281670","https://openalex.org/W3138516171","https://openalex.org/W3196551054","https://openalex.org/W4293846201","https://openalex.org/W4312388283","https://openalex.org/W4312716239","https://openalex.org/W4312933868","https://openalex.org/W4313042219","https://openalex.org/W4313476637","https://openalex.org/W4318954125","https://openalex.org/W4376456710","https://openalex.org/W4385815563","https://openalex.org/W4386065616","https://openalex.org/W4386071537","https://openalex.org/W4386071953","https://openalex.org/W4386075954","https://openalex.org/W4386590781","https://openalex.org/W4388623432","https://openalex.org/W4390872822","https://openalex.org/W4390873054","https://openalex.org/W4390873235","https://openalex.org/W4393146707","https://openalex.org/W4402716075","https://openalex.org/W4402716164","https://openalex.org/W4402716434","https://openalex.org/W4402726899","https://openalex.org/W4402727598","https://openalex.org/W4403422358","https://openalex.org/W4403780693","https://openalex.org/W4403791664","https://openalex.org/W4405183175","https://openalex.org/W4405718359","https://openalex.org/W4408048856","https://openalex.org/W4415797536"],"related_works":[],"abstract_inverted_index":{"Diffusion":[0,70],"models":[1],"have":[2,34,51,138],"made":[3],"tremendous":[4],"progress":[5],"in":[6,181],"generating":[7,113,182],"visually":[8],"realistic":[9],"images.":[10,43,148,185],"However,":[11],"these":[12,49],"images":[13,57,83],"are":[14,171],"statistically":[15],"different":[16],"from":[17,84],"the":[18,45,52,56,59,95,124,135,146,157,160,164,176],"real":[19,147,165],"images,":[20],"which":[21,73,119],"could":[22],"be":[23],"accurately":[24],"classified":[25],"by":[26],"carefully":[27],"designed":[28],"detectors.":[29],"To":[30],"evade":[31],"detection,":[32],"researchers":[33],"proposed":[35,102],"various":[36],"adversarial":[37,98,106,117,136,153,167,183],"example":[38,118],"generation":[39],"schemes":[40,50],"for":[41,103,112],"AI-generated":[42,184],"Despite":[44],"progress,":[46],"most":[47],"of":[48,88,145,163,178],"tendency":[53],"to":[54,76,122,133,143,155,174],"post-process":[55],"and":[58,81,166],"distortion":[60],"is":[61,74,101,110,120],"inevitable.":[62],"In":[63,94],"this":[64],"paper,":[65],"we":[66,127],"propose":[67,128,151],"an":[68,97,105,152],"Adversarial":[69],"Model":[71],"(ADM),":[72],"able":[75,121],"directly":[77],"generate":[78],"high":[79],"quality":[80],"undetectable":[82],"scratch":[85],"on":[86],"top":[87],"a":[89,114,129,139],"pre-trained":[90],"stable":[91],"diffusion":[92],"model.":[93],"ADM,":[96],"denoising":[99],"U-Net":[100],"searching":[104],"latent.":[107],"This":[108],"latent":[109,130],"helpful":[111],"prompt":[115],"consistent":[116],"deceive":[123],"detector.":[125],"Then,":[126],"compensation":[131],"module":[132],"make":[134],"examples":[137],"similar":[140],"reconstruction":[141],"error":[142],"that":[144],"We":[149],"further":[150],"decoder":[154],"minimize":[156],"difference":[158],"between":[159],"high-frequency":[161],"components":[162],"examples.":[168],"Comprehensive":[169],"experiments":[170],"carried":[172],"out":[173],"demonstrate":[175],"advantages":[177],"our":[179],"ADM":[180]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-01-28T00:00:00"}
