{"id":"https://openalex.org/W3161478086","doi":"https://doi.org/10.1109/icpr48806.2021.9412762","title":"Large-Scale Historical Watermark Recognition: dataset and a new consistency-based approach","display_name":"Large-Scale Historical Watermark Recognition: dataset and a new consistency-based approach","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3161478086","doi":"https://doi.org/10.1109/icpr48806.2021.9412762","mag":"3161478086"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9412762","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412762","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-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/A5101938717","display_name":"Xi Shen","orcid":"https://orcid.org/0000-0001-8043-9117"},"institutions":[{"id":"https://openalex.org/I142631665","display_name":"\u00c9cole nationale des ponts et chauss\u00e9es","ror":"https://ror.org/02nwvxz07","country_code":"FR","type":"education","lineage":["https://openalex.org/I142631665","https://openalex.org/I4210145102"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Xi Shen","raw_affiliation_strings":["\u00c9cole des Ponts ParisTech, France"],"affiliations":[{"raw_affiliation_string":"\u00c9cole des Ponts ParisTech, France","institution_ids":["https://openalex.org/I142631665"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032159388","display_name":"Ilaria Pastrolin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210100316","display_name":"\u00c9cole Nationale des Chartes","ror":"https://ror.org/013xvg556","country_code":"FR","type":"education","lineage":["https://openalex.org/I2746051580","https://openalex.org/I4210100316"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Ilaria Pastrolin","raw_affiliation_strings":["\u00c9cole Nationale des Chartes, France"],"affiliations":[{"raw_affiliation_string":"\u00c9cole Nationale des Chartes, France","institution_ids":["https://openalex.org/I4210100316"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071252540","display_name":"Oumayma Bounou","orcid":null},"institutions":[{"id":"https://openalex.org/I142631665","display_name":"\u00c9cole nationale des ponts et chauss\u00e9es","ror":"https://ror.org/02nwvxz07","country_code":"FR","type":"education","lineage":["https://openalex.org/I142631665","https://openalex.org/I4210145102"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Oumayma Bounou","raw_affiliation_strings":["\u00c9cole des Ponts ParisTech, France"],"affiliations":[{"raw_affiliation_string":"\u00c9cole des Ponts ParisTech, France","institution_ids":["https://openalex.org/I142631665"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070809773","display_name":"Spyros Gidaris","orcid":"https://orcid.org/0000-0003-1515-3635"},"institutions":[{"id":"https://openalex.org/I220619192","display_name":"Valeo (France)","ror":"https://ror.org/04ryqpf83","country_code":"FR","type":"company","lineage":["https://openalex.org/I220619192"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Spyros Gidaris","raw_affiliation_strings":["Valeo AI, France"],"affiliations":[{"raw_affiliation_string":"Valeo AI, France","institution_ids":["https://openalex.org/I220619192"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085700775","display_name":"Marc Smith","orcid":"https://orcid.org/0000-0002-6581-9928"},"institutions":[{"id":"https://openalex.org/I4210100316","display_name":"\u00c9cole Nationale des Chartes","ror":"https://ror.org/013xvg556","country_code":"FR","type":"education","lineage":["https://openalex.org/I2746051580","https://openalex.org/I4210100316"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Marc Smith","raw_affiliation_strings":["\u00c9cole Nationale des Chartes, France"],"affiliations":[{"raw_affiliation_string":"\u00c9cole Nationale des Chartes, France","institution_ids":["https://openalex.org/I4210100316"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076151889","display_name":"Olivier Poncet","orcid":"https://orcid.org/0000-0002-3605-4866"},"institutions":[{"id":"https://openalex.org/I4210100316","display_name":"\u00c9cole Nationale des Chartes","ror":"https://ror.org/013xvg556","country_code":"FR","type":"education","lineage":["https://openalex.org/I2746051580","https://openalex.org/I4210100316"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Olivier Poncet","raw_affiliation_strings":["\u00c9cole Nationale des Chartes, France"],"affiliations":[{"raw_affiliation_string":"\u00c9cole Nationale des Chartes, France","institution_ids":["https://openalex.org/I4210100316"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061634216","display_name":"Mathieu Aubry","orcid":"https://orcid.org/0000-0002-3804-0193"},"institutions":[{"id":"https://openalex.org/I142631665","display_name":"\u00c9cole nationale des ponts et chauss\u00e9es","ror":"https://ror.org/02nwvxz07","country_code":"FR","type":"education","lineage":["https://openalex.org/I142631665","https://openalex.org/I4210145102"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Mathieu Aubry","raw_affiliation_strings":["\u00c9cole des Ponts ParisTech, France"],"affiliations":[{"raw_affiliation_string":"\u00c9cole des Ponts ParisTech, France","institution_ids":["https://openalex.org/I142631665"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5101938717"],"corresponding_institution_ids":["https://openalex.org/I142631665"],"apc_list":null,"apc_paid":null,"fwci":0.9689,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.77113315,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"6810","last_page":"6817"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9994000196456909,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9994000196456909,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9976999759674072,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9965000152587891,"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/computer-science","display_name":"Computer science","score":0.8458390235900879},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6896970272064209},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6743992567062378},{"id":"https://openalex.org/keywords/watermark","display_name":"Watermark","score":0.5903929471969604},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.562467098236084},{"id":"https://openalex.org/keywords/sketch","display_name":"Sketch","score":0.5544987320899963},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5392495393753052},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5313839316368103},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4838632345199585},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4834052622318268},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.47331154346466064},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4725750982761383},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44712668657302856},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4200070798397064},{"id":"https://openalex.org/keywords/digital-watermarking","display_name":"Digital watermarking","score":0.41831421852111816},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36255893111228943},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.28429552912712097},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.08845409750938416}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8458390235900879},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6896970272064209},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6743992567062378},{"id":"https://openalex.org/C164112704","wikidata":"https://www.wikidata.org/wiki/Q7974348","display_name":"Watermark","level":3,"score":0.5903929471969604},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.562467098236084},{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.5544987320899963},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5392495393753052},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5313839316368103},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4838632345199585},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4834052622318268},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.47331154346466064},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4725750982761383},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44712668657302856},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4200070798397064},{"id":"https://openalex.org/C150817343","wikidata":"https://www.wikidata.org/wiki/Q875932","display_name":"Digital watermarking","level":3,"score":0.41831421852111816},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36255893111228943},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.28429552912712097},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.08845409750938416},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr48806.2021.9412762","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412762","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4300000071525574,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":73,"referenced_works":["https://openalex.org/W1490862430","https://openalex.org/W1522301498","https://openalex.org/W1579341600","https://openalex.org/W1585641671","https://openalex.org/W1591870335","https://openalex.org/W1722318740","https://openalex.org/W2013034628","https://openalex.org/W2041079134","https://openalex.org/W2063384294","https://openalex.org/W2108444897","https://openalex.org/W2108598243","https://openalex.org/W2115733720","https://openalex.org/W2131846894","https://openalex.org/W2151103935","https://openalex.org/W2194775991","https://openalex.org/W2466618734","https://openalex.org/W2467281799","https://openalex.org/W2472819217","https://openalex.org/W2590953969","https://openalex.org/W2592955078","https://openalex.org/W2601450892","https://openalex.org/W2604763608","https://openalex.org/W2625674597","https://openalex.org/W2753160622","https://openalex.org/W2756073160","https://openalex.org/W2766897166","https://openalex.org/W2768228940","https://openalex.org/W2770468159","https://openalex.org/W2787501667","https://openalex.org/W2796346823","https://openalex.org/W2798836702","https://openalex.org/W2809655762","https://openalex.org/W2883672875","https://openalex.org/W2898012907","https://openalex.org/W2953044442","https://openalex.org/W2962956488","https://openalex.org/W2963275094","https://openalex.org/W2963307918","https://openalex.org/W2963341924","https://openalex.org/W2963391460","https://openalex.org/W2963393306","https://openalex.org/W2963775850","https://openalex.org/W2963845150","https://openalex.org/W2964073646","https://openalex.org/W2964105864","https://openalex.org/W2964121744","https://openalex.org/W2965570799","https://openalex.org/W3012495686","https://openalex.org/W3037856073","https://openalex.org/W3091905774","https://openalex.org/W3102093459","https://openalex.org/W4293412117","https://openalex.org/W4313432866","https://openalex.org/W4387928059","https://openalex.org/W6629277349","https://openalex.org/W6631190155","https://openalex.org/W6635293088","https://openalex.org/W6637542466","https://openalex.org/W6676079856","https://openalex.org/W6681968150","https://openalex.org/W6717367658","https://openalex.org/W6717697761","https://openalex.org/W6720057410","https://openalex.org/W6732703391","https://openalex.org/W6735236233","https://openalex.org/W6736057607","https://openalex.org/W6739364112","https://openalex.org/W6743661861","https://openalex.org/W6746171285","https://openalex.org/W6746260573","https://openalex.org/W6754984195","https://openalex.org/W6783596713","https://openalex.org/W6864424756"],"related_works":["https://openalex.org/W2358156753","https://openalex.org/W2331000677","https://openalex.org/W2019986539","https://openalex.org/W2092308181","https://openalex.org/W1543607864","https://openalex.org/W2069113944","https://openalex.org/W2385739124","https://openalex.org/W2792664837","https://openalex.org/W2025657104","https://openalex.org/W1972559271"],"abstract_inverted_index":{"Historical":[0],"watermark":[1,188],"recognition":[2,85,90,171],"is":[3,103],"a":[4,15,57,131,135,177],"highly":[5],"practical,":[6],"yet":[7],"unsolved":[8],"challenge":[9],"for":[10,43,68,81],"archivists":[11],"and":[12,22,34,86,112,134],"historians.":[13],"With":[14],"large":[16,58,104],"number":[17],"of":[18,27,52,78],"well-defined":[19],"classes,":[20],"cluttered":[21],"noisy":[23],"samples,":[24],"different":[25],"types":[26],"representations,":[28],"both":[29,130],"subtle":[30],"differences":[31],"between":[32],"classes":[33],"high":[35],"intra-class":[36],"variation,":[37],"historical":[38],"watermarks":[39],"are":[40],"also":[41],"challenging":[42,167],"pattern":[44],"recognition.":[45],"In":[46,185],"this":[47,100],"paper,":[48],"overcoming":[49],"the":[50,69,76,181],"difficulty":[51],"data":[53],"collection,":[54],"we":[55,128,190],"present":[56],"public":[59],"dataset":[60,102],"with":[61],"more":[62,92],"than":[63,93],"6k":[64],"new":[65,101],"photographs,":[66],"allowing":[67],"first":[70],"time":[71],"to":[72,106,155,187],"tackle":[73],"at":[74],"scale":[75],"scenarios":[77],"practical":[79],"interest":[80],"scholars:":[82],"one-shot":[83,88,169],"instance":[84,89],"cross-domain":[87,170],"amongst":[91],"16k":[94],"fine-grained":[95,198],"classes.":[96],"We":[97],"demonstrate":[98],"that":[99,114],"enough":[105],"train":[107],"modern":[108],"deep":[109,124],"learning":[110],"approaches,":[111],"show":[113,191],"standard":[115],"methods":[116],"can":[117],"be":[118],"improved":[119],"considerably":[120],"by":[121,176],"using":[122,144],"mid-level":[123],"features.":[125],"More":[126],"precisely,":[127],"design":[129],"matching":[132],"score":[133],"feature":[136],"fine-tuning":[137],"strategy":[138],"based":[139],"on":[140,164,197],"filtering":[141],"local":[142],"matches":[143],"spatial":[145],"consistency.":[146],"This":[147],"consistency-based":[148],"approach":[149,193],"provides":[150,194],"important":[151],"performance":[152],"boost":[153],"compared":[154],"strong":[156],"baselines.":[157],"Our":[158],"model":[159],"achieves":[160],"55%":[161],"top-1":[162],"accuracy":[163],"our":[165,192],"very":[166],"16,753-class":[168],"task,":[172],"each":[173],"class":[174],"described":[175],"single":[178],"drawing":[179],"from":[180],"classic":[182],"Briquet":[183],"catalog.":[184],"addition":[186],"classification,":[189],"promising":[195],"results":[196],"sketch-based":[199],"image":[200],"retrieval.":[201]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2019,"cited_by_count":1}],"updated_date":"2026-03-28T08:17:26.163206","created_date":"2025-10-10T00:00:00"}
