{"id":"https://openalex.org/W7161676593","doi":"https://doi.org/10.48550/arxiv.2605.16720","title":"Compositional Adversarial Training for Robust Visual Watermarking","display_name":"Compositional Adversarial Training for Robust Visual Watermarking","publication_year":2026,"publication_date":"2026-05-16","ids":{"openalex":"https://openalex.org/W7161676593","doi":"https://doi.org/10.48550/arxiv.2605.16720"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.16720","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.16720","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.2605.16720","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136493450","display_name":"Anirudh Satheesh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Satheesh, Anirudh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136489557","display_name":"Michael-Andrei Panaitescu-Liess","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Panaitescu-Liess, Michael-Andrei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136500591","display_name":"Andrew Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Andrew","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136455277","display_name":"Georgios Milis","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Milis, Georgios","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136477215","display_name":"Heng Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Heng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063977912","display_name":"Zikui Cai","orcid":"https://orcid.org/0000-0003-1663-9493"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cai, Zikui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136480726","display_name":"Furong Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Furong","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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.4771000146865845,"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":0.4771000146865845,"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/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.3319999873638153,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.06759999692440033,"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/digital-watermarking","display_name":"Digital watermarking","score":0.8399999737739563},{"id":"https://openalex.org/keywords/watermark","display_name":"Watermark","score":0.6572999954223633},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6345000267028809},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5284000039100647},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.5188999772071838},{"id":"https://openalex.org/keywords/adversary","display_name":"Adversary","score":0.4291999936103821},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.4187000095844269},{"id":"https://openalex.org/keywords/steganography","display_name":"Steganography","score":0.37779998779296875}],"concepts":[{"id":"https://openalex.org/C150817343","wikidata":"https://www.wikidata.org/wiki/Q875932","display_name":"Digital watermarking","level":3,"score":0.8399999737739563},{"id":"https://openalex.org/C164112704","wikidata":"https://www.wikidata.org/wiki/Q7974348","display_name":"Watermark","level":3,"score":0.6572999954223633},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6345000267028809},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.588100016117096},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5284000039100647},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.5188999772071838},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5184999704360962},{"id":"https://openalex.org/C41065033","wikidata":"https://www.wikidata.org/wiki/Q2825412","display_name":"Adversary","level":2,"score":0.4291999936103821},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.4187000095844269},{"id":"https://openalex.org/C108801101","wikidata":"https://www.wikidata.org/wiki/Q15032","display_name":"Steganography","level":3,"score":0.37779998779296875},{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.36149999499320984},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35339999198913574},{"id":"https://openalex.org/C122760801","wikidata":"https://www.wikidata.org/wiki/Q2552011","display_name":"Watermarking attack","level":5,"score":0.3434999883174896},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33399999141693115},{"id":"https://openalex.org/C178489894","wikidata":"https://www.wikidata.org/wiki/Q8789","display_name":"Cryptography","level":2,"score":0.3174000084400177},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.31209999322891235},{"id":"https://openalex.org/C65856478","wikidata":"https://www.wikidata.org/wiki/Q3991682","display_name":"Attack model","level":2,"score":0.3061999976634979},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30140000581741333},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.296999990940094},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2937999963760376},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2906000018119812},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.2694000005722046},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.26739999651908875},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.2639000117778778}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.16720","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.16720","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.2605.16720","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.16720","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","score":0.7834511399269104,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Robust":[0],"watermarking":[1,219],"is":[2],"typically":[3],"trained":[4,161],"with":[5,96,162,167],"random":[6,10,230],"post-processing":[7],"augmentation,":[8],"but":[9],"sampling":[11],"under-covers":[12],"the":[13,23,72,100,163,168,187,194,198,203],"combinatorial":[14],"space":[15,51],"of":[16,52],"realistic":[17],"attack":[18,79,94,112,123,145,189],"pipelines":[19],"and":[20,35,76,107,135,137,143,149,153,175,191],"rarely":[21],"encounters":[22],"rare":[24],"compositions":[25],"that":[26,64,70,216],"actually":[27],"break":[28],"detection.":[29],"This":[30],"leads":[31],"to":[32,84,103,120,184],"unstable":[33],"training":[34,222],"poor":[36],"sample":[37],"efficiency.":[38],"We":[39,55,125],"instead":[40],"formulate":[41],"watermark":[42,180],"robustness":[43],"as":[44],"a":[45,49,61,66,91,121],"min-max":[46],"problem":[47],"over":[48],"structured":[50],"compositional":[53,195,225],"transformations.":[54,212],"propose":[56],"Compositional":[57],"Adversarial":[58],"Training":[59],"(CAT),":[60],"plug-in":[62],"framework":[63],"learns":[65],"sequential":[67],"differentiable":[68,106],"adversary":[69],"observes":[71],"current":[73],"watermarked":[74],"image":[75,152],"selects":[77],"an":[78],"family":[80],"at":[81],"each":[82],"step":[83],"maximally":[85],"disrupt":[86],"message":[87],"recovery.":[88],"CAT":[89,127,156,201],"combines":[90],"straight-through":[92],"Gumbel-Softmax":[93],"selection":[95],"entropy":[97],"regularization,":[98],"allowing":[99],"backward":[101],"pass":[102],"be":[104],"end-to-end":[105],"aggregate":[108],"gradient":[109],"information":[110],"across":[111],"families,":[113],"yielding":[114],"faster,":[115],"smoother":[116],"convergence":[117],"without":[118],"collapsing":[119],"single":[122],"mode.":[124],"evaluate":[126],"on":[128,147,171,207,209],"post-generation":[129],"watermarks":[130],"VideoSeal":[131,133],"0.0,":[132],"1.0,":[134],"PixelSeal":[136],"in-generation":[138],"WMAR":[139],"under":[140],"both":[141],"single-step":[142,188],"two-step":[144],"suites,":[146],"in-distribution":[148],"multiple":[150],"out-of-distribution":[151],"video":[154],"benchmarks.":[155],"consistently":[157],"outperforms":[158],"random-augmentation":[159],"baselines":[160],"same":[164],"augmentation":[165],"budget,":[166],"largest":[169],"gains":[170],"hard":[172],"composed":[173],"attacks":[174],"OOD":[176],"evaluations;":[177],"improving":[178],"overall":[179],"capacity":[181],"by":[182,205],"up":[183],"$63.5\\%$":[185],"in":[186,193],"setting":[190],"$13.0\\%$":[192],"setting.":[196],"In":[197],"autoregressive":[199],"setting,":[200],"improves":[202],"TPR@FPR$=1\\%$":[204],"$12\\%$":[206],"average":[208],"difficult":[210],"geometric":[211],"These":[213],"results":[214],"show":[215],"robust":[217],"visual":[218],"benefits":[220],"from":[221],"against":[223],"adaptive":[224],"adversaries":[226],"rather":[227],"than":[228],"independent":[229],"corruptions.":[231]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-20T00:00:00"}