{"id":"https://openalex.org/W7154473419","doi":"https://doi.org/10.48550/arxiv.2604.12941","title":"Direct Discrepancy Replay: Distribution-Discrepancy Condensation and Manifold-Consistent Replay for Continual Face Forgery Detection","display_name":"Direct Discrepancy Replay: Distribution-Discrepancy Condensation and Manifold-Consistent Replay for Continual Face Forgery Detection","publication_year":2026,"publication_date":"2026-04-14","ids":{"openalex":"https://openalex.org/W7154473419","doi":"https://doi.org/10.48550/arxiv.2604.12941"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.12941","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.12941","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.12941","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133685334","display_name":"Tianshuo Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Tianshuo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133662260","display_name":"Haoyuan Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Haoyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081847796","display_name":"Siran Peng","orcid":"https://orcid.org/0000-0002-3983-5596"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peng, Siran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014417853","display_name":"Weisong Zhao","orcid":"https://orcid.org/0000-0003-3957-8590"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Weisong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133636195","display_name":"Xiangyu Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Xiangyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133678613","display_name":"Zhen Lei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lei, Zhen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.3160000145435333,"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/T11448","display_name":"Face recognition and analysis","score":0.3160000145435333,"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":0.2648000121116638,"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":0.18199999630451202,"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/leverage","display_name":"Leverage (statistics)","score":0.5720999836921692},{"id":"https://openalex.org/keywords/forgetting","display_name":"Forgetting","score":0.5152000188827515},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.43299999833106995},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.42480000853538513},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.3828999996185303},{"id":"https://openalex.org/keywords/replay-attack","display_name":"Replay attack","score":0.37299999594688416}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7753000259399414},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5720999836921692},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.5152000188827515},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.43299999833106995},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.42480000853538513},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.3828999996185303},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3752000033855438},{"id":"https://openalex.org/C11560541","wikidata":"https://www.wikidata.org/wiki/Q1756025","display_name":"Replay attack","level":3,"score":0.37299999594688416},{"id":"https://openalex.org/C2779137570","wikidata":"https://www.wikidata.org/wiki/Q16243196","display_name":"EXPOSE","level":2,"score":0.36629998683929443},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.31779998540878296},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.29739999771118164},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.26249998807907104},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.2578999996185303}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.12941","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.12941","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.12941","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.12941","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.7929830551147461}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Continual":[0],"face":[1,202],"forgery":[2,10,62,96,180],"detection":[3],"(CFFD)":[4],"requires":[5],"detectors":[6],"to":[7,30,75,90,122,226],"learn":[8],"emerging":[9],"paradigms":[11],"without":[12,197],"forgetting":[13],"previously":[14],"seen":[15],"manipulations.":[16],"Existing":[17],"CFFD":[18,88,209],"methods":[19],"commonly":[20],"rely":[21],"on":[22],"replaying":[23],"a":[24,41,138,148],"small":[25,193],"amount":[26],"of":[27,85,94,151,168],"past":[28,76],"data":[29],"mitigate":[31],"forgetting.":[32,215],"Such":[33],"replay":[34,86,163],"is":[35,89],"typically":[36],"implemented":[37],"either":[38],"by":[39,46],"storing":[40,199],"few":[42],"historical":[43,201],"samples":[44,164,176],"or":[45],"synthesizing":[47],"pseudo-forgeries":[48],"from":[49,118],"detector-dependent":[50],"perturbations.":[51],"Under":[52],"strict":[53],"memory":[54,194],"budgets,":[55],"the":[56,70,82,92,107,119,134],"former":[57],"cannot":[58],"adequately":[59],"cover":[60],"diverse":[61],"cues":[63,181],"and":[64,111,114,144,196,211],"may":[65],"expose":[66],"facial":[67],"identities,":[68],"while":[69,182],"latter":[71],"remains":[72],"strongly":[73],"tied":[74],"decision":[77],"boundaries.":[78],"We":[79,155],"argue":[80],"that":[81,177],"core":[83],"role":[84],"in":[87,141],"reinstate":[91],"distributions":[93,113],"previous":[95],"tasks":[97],"during":[98],"subsequent":[99],"training.":[100],"To":[101],"this":[102],"end,":[103],"we":[104,127],"directly":[105,198],"condense":[106],"discrepancy":[108,136,153],"between":[109],"real":[110,116,173],"fake":[112],"leverage":[115],"faces":[117],"current":[120,186],"stage":[121],"perform":[123],"distribution-level":[124],"replay.":[125,228],"Specifically,":[126],"introduce":[128],"Distribution-Discrepancy":[129],"Condensation":[130],"(DDC),":[131],"which":[132,161],"models":[133],"real-to-fake":[135],"via":[137],"surrogate":[139],"factorization":[140],"characteristic-function":[142],"space":[143],"condenses":[145],"it":[146],"into":[147],"tiny":[149],"bank":[150],"distribution":[152],"maps.":[154],"further":[156,219],"propose":[157],"Manifold-Consistent":[158],"Replay":[159],"(MCR),":[160],"synthesizes":[162],"through":[165],"variance-preserving":[166],"composition":[167],"these":[169],"maps":[170],"with":[171,185],"current-stage":[172],"faces,":[174],"yielding":[175],"reflect":[178],"previous-task":[179],"remaining":[183],"compatible":[184],"real-face":[187],"statistics.":[188],"Operating":[189],"under":[190],"an":[191],"extremely":[192],"budget":[195],"raw":[200],"images,":[203],"our":[204],"framework":[205],"consistently":[206],"outperforms":[207],"prior":[208],"baselines":[210],"significantly":[212],"mitigates":[213],"catastrophic":[214],"Replay-level":[216],"privacy":[217],"analysis":[218],"suggests":[220],"reduced":[221],"identity":[222],"leakage":[223],"risk":[224],"relative":[225],"selection-based":[227]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-04-16T00:00:00"}
