{"id":"https://openalex.org/W7163514023","doi":"https://doi.org/10.48550/arxiv.2606.04545","title":"Impostor: An Agent-Curated Benchmark for Realistic AIGC Manipulation Localization","display_name":"Impostor: An Agent-Curated Benchmark for Realistic AIGC Manipulation Localization","publication_year":2026,"publication_date":"2026-06-03","ids":{"openalex":"https://openalex.org/W7163514023","doi":"https://doi.org/10.48550/arxiv.2606.04545"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.04545","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.04545","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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.2606.04545","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137907560","display_name":"Zhenliang Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Zhenliang","raw_affiliation_strings":["Southeast University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southeast University","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137837688","display_name":"Yutao Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Yutao","raw_affiliation_strings":["Southeast University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southeast University","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024164148","display_name":"Qixiong Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Qixiong","raw_affiliation_strings":["Xiaohongshu Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xiaohongshu Inc","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137907516","display_name":"Wenpeng Du","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Du, Wenpeng","raw_affiliation_strings":["Southeast University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southeast University","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137849728","display_name":"Hongxiang Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Hongxiang","raw_affiliation_strings":["Xiaohongshu Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xiaohongshu Inc","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137832620","display_name":"Jiasong Wu","orcid":"https://orcid.org/0000-0001-7171-1318"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Jiasong","raw_affiliation_strings":["Southeast University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southeast University","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137842094","display_name":"Xiaolong Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Xiaolong","raw_affiliation_strings":["Xiaohongshu Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xiaohongshu Inc","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5137888180","display_name":"Jungong Han","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Han, Jungong","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9230999946594238,"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":0.9230999946594238,"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":0.055799998342990875,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.002099999925121665,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6657999753952026},{"id":"https://openalex.org/keywords/controllability","display_name":"Controllability","score":0.6245999932289124},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.5960000157356262},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5799999833106995},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5656999945640564},{"id":"https://openalex.org/keywords/image-editing","display_name":"Image editing","score":0.5295000076293945},{"id":"https://openalex.org/keywords/image-manipulation","display_name":"Image manipulation","score":0.4740000069141388},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.39750000834465027}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7847999930381775},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6708999872207642},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6657999753952026},{"id":"https://openalex.org/C48209547","wikidata":"https://www.wikidata.org/wiki/Q1331104","display_name":"Controllability","level":2,"score":0.6245999932289124},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.5960000157356262},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5799999833106995},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5656999945640564},{"id":"https://openalex.org/C2776674983","wikidata":"https://www.wikidata.org/wiki/Q545981","display_name":"Image editing","level":3,"score":0.5295000076293945},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4749999940395355},{"id":"https://openalex.org/C2987933465","wikidata":"https://www.wikidata.org/wiki/Q141130","display_name":"Image manipulation","level":3,"score":0.4740000069141388},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.39750000834465027},{"id":"https://openalex.org/C2989087649","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Image synthesis","level":3,"score":0.39719998836517334},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.36559998989105225},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3634999990463257},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3610000014305115},{"id":"https://openalex.org/C2779982483","wikidata":"https://www.wikidata.org/wiki/Q6094420","display_name":"Iterative refinement","level":2,"score":0.3353999853134155},{"id":"https://openalex.org/C65682993","wikidata":"https://www.wikidata.org/wiki/Q1056451","display_name":"Reflection (computer programming)","level":2,"score":0.3181999921798706},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3050999939441681},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.30149999260902405},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.29490000009536743},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2630999982357025},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2565000057220459}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.04545","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.04545","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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.2606.04545","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.04545","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.6451295614242554}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2,33,48],"generative":[3],"image":[4,14,20,49,61],"editing":[5,82],"have":[6,31],"improved":[7],"the":[8],"realism":[9],"and":[10,23,38,88,95,114,140,168,179],"controllability":[11],"of":[12],"localized":[13],"manipulation,":[15],"raising":[16],"new":[17],"challenges":[18,161],"for":[19,124],"manipulation":[21,36,62,84,112],"detection":[22],"localization":[24,63],"(IMDL).":[25],"However,":[26],"existing":[27,163],"IMDL":[28,170],"benchmarks":[29],"still":[30],"limitations":[32],"visual":[34],"realism,":[35],"diversity,":[37],"generator":[39],"coverage,":[40],"making":[41],"it":[42],"difficult":[43],"to":[44,91,144,162],"reflect":[45],"recent":[46,107],"trends":[47],"manipulation.":[50],"To":[51],"address":[52],"these":[53],"limitations,":[54],"we":[55,128],"introduce":[56],"Impostor,":[57],"a":[58,74,120,132],"high-quality":[59],"AI-edited":[60],"dataset":[64],"containing":[65],"100K":[66],"manipulated":[67,98,117,152],"images.":[68,99],"Impostor":[69,101,158,178],"is":[70],"constructed":[71],"by":[72,105],"CraftAgent,":[73],"closed-loop":[75],"agent":[76],"framework":[77,134],"that":[78,135,157],"integrates":[79],"scene":[80],"perception,":[81],"planning,":[83],"execution,":[85],"quality":[86],"validation,":[87],"iterative":[89],"reflection":[90],"automatically":[92],"generate":[93],"diverse":[94],"visually":[96],"realistic":[97],"Moreover,":[100],"contains":[102],"images":[103],"generated":[104],"seven":[106],"AIGC":[108],"models":[109,166],"across":[110],"three":[111],"types":[113],"includes":[115],"multiple":[116,180],"regions,":[118],"providing":[119],"more":[121],"comprehensive":[122],"benchmark":[123],"AIGC-based":[125],"IMDL.":[126],"Furthermore,":[127],"propose":[129],"PhaseAware-Net":[130],"(PANet),":[131],"semantic-forensic":[133,141],"introduces":[136],"local":[137],"phase":[138],"modeling":[139],"consistency":[142],"learning":[143],"better":[145],"localize":[146],"semantically":[147],"plausible":[148],"yet":[149],"forensically":[150],"disrupted":[151],"regions.":[153],"Extensive":[154],"experiments":[155],"show":[156],"poses":[159],"significant":[160],"large":[164],"vision-language":[165],"(LVLMs)":[167],"specialized":[169],"methods,":[171],"while":[172],"PANet":[173],"achieves":[174],"superior":[175],"performance":[176],"on":[177],"public":[181],"benchmarks.":[182]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-05T00:00:00"}
