{"id":"https://openalex.org/W7147076598","doi":"https://doi.org/10.48550/arxiv.2603.27513","title":"Understanding Semantic Perturbations on In-Processing Generative Image Watermarks","display_name":"Understanding Semantic Perturbations on In-Processing Generative Image Watermarks","publication_year":2026,"publication_date":"2026-03-29","ids":{"openalex":"https://openalex.org/W7147076598","doi":"https://doi.org/10.48550/arxiv.2603.27513"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.27513","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.27513","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.27513","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5132643485","display_name":"Anirudh Nakra","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Nakra, Anirudh","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5132647869","display_name":"Min Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Min","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5132643485"],"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.5989999771118164,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.5989999771118164,"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/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.08839999884366989,"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":0.065700002014637,"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/robustness","display_name":"Robustness (evolution)","score":0.7635999917984009},{"id":"https://openalex.org/keywords/digital-watermarking","display_name":"Digital watermarking","score":0.6751999855041504},{"id":"https://openalex.org/keywords/watermark","display_name":"Watermark","score":0.6312000155448914},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5849000215530396},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5582000017166138},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5062999725341797},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.42969998717308044}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7635999917984009},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7142999768257141},{"id":"https://openalex.org/C150817343","wikidata":"https://www.wikidata.org/wiki/Q875932","display_name":"Digital watermarking","level":3,"score":0.6751999855041504},{"id":"https://openalex.org/C164112704","wikidata":"https://www.wikidata.org/wiki/Q7974348","display_name":"Watermark","level":3,"score":0.6312000155448914},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5864999890327454},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5849000215530396},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5582000017166138},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5062999725341797},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.42969998717308044},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40950000286102295},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.37720000743865967},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3564000129699707},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.34209999442100525},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.32429999113082886},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.3142000138759613},{"id":"https://openalex.org/C11727466","wikidata":"https://www.wikidata.org/wiki/Q1628157","display_name":"Inpainting","level":3,"score":0.30709999799728394},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28760001063346863},{"id":"https://openalex.org/C86034646","wikidata":"https://www.wikidata.org/wiki/Q474311","display_name":"Semantic gap","level":4,"score":0.2768000066280365}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.27513","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.27513","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.27513","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.27513","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":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,88],"widespread":[1],"deployment":[2],"of":[3,129,142],"high-fidelity":[4],"generative":[5,26,83],"models":[6,92],"has":[7,30],"intensified":[8],"the":[9,25,127],"need":[10],"for":[11,14,79,93,186],"reliable":[12],"mechanisms":[13],"provenance":[15],"and":[16,36,50,98,176,181],"content":[17,61],"authentication.":[18],"In-processing":[19],"watermarking,":[20],"embedding":[21],"a":[22,34,75,139,169],"signature":[23],"into":[24],"model's":[27],"synthesis":[28],"procedure,":[29],"been":[31],"advocated":[32],"as":[33,47],"solution":[35],"is":[37,67],"often":[38],"reported":[39],"to":[40,43,54,104,157],"be":[41],"robust":[42],"standard":[44],"post-processing":[45],"(such":[46],"geometric":[48],"transforms":[49],"filtering).":[51],"Yet":[52],"robustness":[53,123,187],"semantic":[55,86,130,148,189],"manipulations":[56],"that":[57,122,178],"alter":[58],"high-level":[59],"scene":[60],"while":[62,160],"maintaining":[63],"reasonable":[64],"visual":[65],"quality":[66,162],"not":[68],"well":[69],"studied":[70],"or":[71,102],"understood.":[72],"We":[73],"introduce":[74],"simple,":[76],"multi-stage":[77],"framework":[78,89],"systematically":[80],"stress-testing":[81],"in-processing":[82],"watermarks":[84,135],"under":[85,138,147],"drift.":[87],"utilizes":[90],"off-the-shelf":[91],"object":[94],"detection,":[95],"mask":[96],"generation,":[97],"semantically":[99],"guided":[100],"inpainting":[101],"regeneration":[103],"produce":[105],"controlled,":[106],"meaning-altering":[107],"edits":[108],"with":[109,126,150],"minimal":[110],"perceptual":[111],"degradation.":[112],"Based":[113],"on":[114,117],"extensive":[115],"experiments":[116],"representative":[118],"schemes,":[119],"we":[120],"find":[121],"varies":[124],"significantly":[125],"degree":[128],"entanglement:":[131],"methods":[132],"by":[133],"which":[134],"remain":[136],"detectable":[137],"broad":[140],"suite":[141],"conventional":[143],"perturbations":[144],"can":[145],"fail":[146],"edits,":[149],"watermark":[151,179],"detectability":[152],"in":[153,172],"many":[154],"cases":[155],"dropping":[156],"near":[158],"zero":[159],"image":[161],"remains":[163],"high.":[164],"Overall,":[165],"our":[166],"results":[167],"reveal":[168],"critical":[170],"gap":[171],"current":[173],"watermarking":[174],"evaluations":[175],"suggest":[177],"designs":[180],"benchmarking":[182],"must":[183],"explicitly":[184],"account":[185],"against":[188],"manipulation.":[190]},"counts_by_year":[],"updated_date":"2026-04-02T13:53:19.096889","created_date":"2026-04-02T00:00:00"}