{"id":"https://openalex.org/W7169767205","doi":"https://doi.org/10.48550/arxiv.2607.15734","title":"The Third Competition on Document Forgery Detection on ID-Cards and Passports","display_name":"The Third Competition on Document Forgery Detection on ID-Cards and Passports","publication_year":2026,"publication_date":"2026-07-17","ids":{"openalex":"https://openalex.org/W7169767205","doi":"https://doi.org/10.48550/arxiv.2607.15734"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.15734","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.15734","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.2607.15734","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017736954","display_name":"Juan Tapia","orcid":"https://orcid.org/0000-0001-9159-4075"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tapia, Juan E.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103412093","display_name":"M Susana Nieto","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nieto, Mario","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5141206105","display_name":"Juan M. Espin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Espin, Juan M.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113407782","display_name":"Alvaro S. Rocamora","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rocamora, \u00c1lvaro S.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060250724","display_name":"Javier Barrachina","orcid":"https://orcid.org/0009-0003-4074-3140"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Barrachina, Javier","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059766088","display_name":"Naser Damer","orcid":"https://orcid.org/0000-0001-7910-7895"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Damer, Naser","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5141197629","display_name":"Christoph Busch","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Busch, Christoph","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/T12357","display_name":"Digital Media Forensic Detection","score":0.683899998664856,"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":0.683899998664856,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.12430000305175781,"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/T12034","display_name":"Digital and Cyber Forensics","score":0.042100001126527786,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/competition","display_name":"Competition (biology)","score":0.7305999994277954},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.703499972820282},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6241999864578247},{"id":"https://openalex.org/keywords/track","display_name":"Track (disk drive)","score":0.6054999828338623},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.5906000137329102},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.5052000284194946}],"concepts":[{"id":"https://openalex.org/C91306197","wikidata":"https://www.wikidata.org/wiki/Q45767","display_name":"Competition (biology)","level":2,"score":0.7305999994277954},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.703499972820282},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6241999864578247},{"id":"https://openalex.org/C89992363","wikidata":"https://www.wikidata.org/wiki/Q5961558","display_name":"Track (disk drive)","level":2,"score":0.6054999828338623},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.597000002861023},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.5906000137329102},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.5052000284194946},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.48080000281333923},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.3384999930858612},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.33799999952316284},{"id":"https://openalex.org/C2983583741","wikidata":"https://www.wikidata.org/wiki/Q16785388","display_name":"Third party","level":2,"score":0.2955999970436096},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.2953999936580658},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.28529998660087585},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.2709999978542328},{"id":"https://openalex.org/C2776736423","wikidata":"https://www.wikidata.org/wiki/Q326498","display_name":"Competition law","level":3,"score":0.2619999945163727},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2542000114917755}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.15734","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.15734","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.2607.15734","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.15734","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0,137,153],"paper":[1],"presents":[2],"a":[3,32,61,158],"comprehensive":[4],"analysis":[5],"of":[6,49,60,88,121,130],"the":[7,10,42,58,68,82,128,168],"results":[8,99],"from":[9],"Third":[11],"International":[12],"Competition":[13],"on":[14,18,164],"Document":[15],"Forgery":[16],"Detection":[17],"ID-Cards":[19],"and":[20,56,95,116,134,145,173],"Passports,":[21],"which":[22],"was":[23],"held":[24],"across":[25,54,75,90,112,124],"two":[26],"distinct":[27],"tracks.":[28],"Track":[29,66],"1":[30],"evaluates":[31],"synthetic-data-based":[33],"ID-PAD":[34],"system":[35],"under":[36],"controlled":[37],"but":[38,109],"diverse":[39,113],"conditions,":[40],"where":[41,78],"winning":[43],"team,":[44],"\\textit{Incode},":[45],"achieves":[46],"an":[47,86],"$AV_{Rank}$":[48,87],"27.82%,":[50],"confirming":[51],"consistent":[52],"performance":[53],"metrics":[55],"highlighting":[57],"importance":[59],"balanced,":[62],"generalizable":[63],"design.":[64],"In":[65],"2,":[67],"challenge":[69],"intensifies":[70],"with":[71,85],"heterogeneous":[72],"attack":[73,114],"scenarios":[74],"different":[76],"domains,":[77],"\\textit{Incode}":[79],"again":[80],"achieved":[81],"top":[83],"position":[84],"68.71%":[89],"thresholds,":[91],"outperforming":[92],"some":[93],"baselines":[94],"established":[96],"methods.":[97],"These":[98],"demonstrate":[100],"that":[101],"PAD":[102,163],"effectiveness":[103],"requires":[104],"not":[105],"only":[106],"high":[107],"accuracy":[108],"also":[110],"consistency":[111],"types":[115],"imaging":[117],"conditions.":[118],"The":[119],"success":[120],"this":[122],"initiative":[123],"both":[125],"tracks":[126],"underscores":[127],"value":[129],"collaboration":[131],"between":[132],"companies":[133],"academic":[135],"teams.":[136],"year,":[138],"more":[139,146],"than":[140,147],"\\textit{63":[141],"teams}":[142],"were":[143,151],"registered,":[144],"\\textit{100":[148],"submission":[149],"models}":[150],"evaluated.":[152],"competition":[154],"has":[155],"evolved":[156],"into":[157],"leading":[159],"benchmark":[160],"state-of-the-art":[161],"in":[162,176],"ID":[165],"documents,":[166],"setting":[167],"standard":[169],"for":[170],"performance,":[171],"reproducibility,":[172],"real-world":[174],"applicability":[175],"secure":[177],"identity":[178],"verification.":[179]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-21T00:00:00"}