{"id":"https://openalex.org/W3199670999","doi":"https://doi.org/10.1007/978-3-030-86549-8_18","title":"SmartPatch: Improving Handwritten Word Imitation with Patch Discriminators","display_name":"SmartPatch: Improving Handwritten Word Imitation with Patch Discriminators","publication_year":2021,"publication_date":"2021-05-21","ids":{"openalex":"https://openalex.org/W3199670999","doi":"https://doi.org/10.1007/978-3-030-86549-8_18","mag":"3199670999"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2105.10528","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2105.10528","pdf_url":"https://arxiv.org/pdf/2105.10528","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"book-chapter","indexed_in":["arxiv"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2105.10528","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015218576","display_name":"Alexander Mattick","orcid":"https://orcid.org/0000-0001-7805-199X"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Mattick, Alexander","raw_affiliation_strings":["Pattern Recognition Lab, Friedrich-Alexander University Erlangen, N\u00fcrnberg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pattern Recognition Lab, Friedrich-Alexander University Erlangen, N\u00fcrnberg, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063384241","display_name":"Martin Mayr","orcid":"https://orcid.org/0000-0002-3706-285X"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Mayr, Martin","raw_affiliation_strings":["Pattern Recognition Lab, Friedrich-Alexander University Erlangen, N\u00fcrnberg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pattern Recognition Lab, Friedrich-Alexander University Erlangen, N\u00fcrnberg, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066134818","display_name":"Mathias Seuret","orcid":"https://orcid.org/0000-0001-9153-1031"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Seuret, Mathias","raw_affiliation_strings":["Pattern Recognition Lab, Friedrich-Alexander University Erlangen, N\u00fcrnberg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pattern Recognition Lab, Friedrich-Alexander University Erlangen, N\u00fcrnberg, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101619735","display_name":"Andreas Maier","orcid":"https://orcid.org/0000-0002-9550-5284"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Maier, Andreas","raw_affiliation_strings":["Pattern Recognition Lab, Friedrich-Alexander University Erlangen, N\u00fcrnberg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pattern Recognition Lab, Friedrich-Alexander University Erlangen, N\u00fcrnberg, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087093169","display_name":"Vincent Christlein","orcid":"https://orcid.org/0000-0003-0455-3799"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Christlein, Vincent","raw_affiliation_strings":["Pattern Recognition Lab, Friedrich-Alexander University Erlangen, N\u00fcrnberg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pattern Recognition Lab, Friedrich-Alexander University Erlangen, N\u00fcrnberg, Germany","institution_ids":["https://openalex.org/I181369854"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I181369854"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":25,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9959999918937683,"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":0.9937999844551086,"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":0.8774192333221436},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.6624156832695007},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.6397294402122498},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5708767175674438},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5231351256370544},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.47166693210601807},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3471468687057495}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8774192333221436},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6624156832695007},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.6397294402122498},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5708767175674438},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5231351256370544},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.47166693210601807},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3471468687057495},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:arXiv.org:2105.10528","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2105.10528","pdf_url":"https://arxiv.org/pdf/2105.10528","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2105.10528","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2105.10528","pdf_url":"https://arxiv.org/pdf/2105.10528","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7400000095367432,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W592244745","https://openalex.org/W1686810756","https://openalex.org/W1810943226","https://openalex.org/W2099471712","https://openalex.org/W2117539524","https://openalex.org/W2152928267","https://openalex.org/W2183341477","https://openalex.org/W2603777577","https://openalex.org/W2617973426","https://openalex.org/W2784512264","https://openalex.org/W2907770449","https://openalex.org/W2913752175","https://openalex.org/W2962835968","https://openalex.org/W2963073614","https://openalex.org/W2963981733","https://openalex.org/W2964199361","https://openalex.org/W3003428515","https://openalex.org/W3013377786","https://openalex.org/W3034904792","https://openalex.org/W3082823856","https://openalex.org/W3109645351","https://openalex.org/W3126649386","https://openalex.org/W3128933103","https://openalex.org/W4288574863","https://openalex.org/W4301206121","https://openalex.org/W4320013936"],"related_works":["https://openalex.org/W4293202849","https://openalex.org/W1980965563","https://openalex.org/W1489300767","https://openalex.org/W2387995142","https://openalex.org/W4380714744","https://openalex.org/W4319453655","https://openalex.org/W2089959425","https://openalex.org/W2057775761","https://openalex.org/W1608433645","https://openalex.org/W2296205523"],"abstract_inverted_index":{"As":[0],"of":[1,14,23,31,63,101],"recent":[2],"generative":[3],"adversarial":[4],"networks":[5],"have":[6],"allowed":[7],"for":[8,42],"big":[9],"leaps":[10],"in":[11,17,45,114],"the":[12,21,61,69,82,90,98,102],"realism":[13],"generated":[15,119],"images":[16],"diverse":[18],"domains,":[19],"not":[20],"least":[22],"which":[24],"being":[25],"handwritten":[26,46,93,120],"text":[27,34,47,94],"generation.":[28],"The":[29],"generation":[30],"realistic-looking":[32],"hand-written":[33],"is":[35],"important":[36],"because":[37],"it":[38],"can":[39],"be":[40],"used":[41],"data":[43],"augmentation":[44],"recognition":[48,95],"(HTR)":[49],"systems":[50],"or":[51],"human-computer":[52],"interaction.":[53],"We":[54,80],"propose":[55],"SmartPatch,":[56],"a":[57,73,107],"new":[58],"technique":[59],"increasing":[60],"performance":[62],"current":[64],"state-of-the-art":[65],"methods":[66],"by":[67],"augmenting":[68],"training":[70],"feedback":[71],"with":[72,86],"tailored":[74],"solution":[75],"to":[76,106],"mitigate":[77],"pen-level":[78],"artifacts.":[79],"combine":[81],"well-known":[83],"patch":[84],"loss":[85],"information":[87],"gathered":[88],"from":[89],"parallel":[91],"trained":[92],"system":[96],"and":[97,112,117],"separate":[99],"characters":[100],"word.":[103],"This":[104],"leads":[105],"more":[108,115],"enhanced":[109],"local":[110],"discriminator":[111],"results":[113],"realistic":[116],"higher-quality":[118],"words.":[121]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":5}],"updated_date":"2026-07-03T06:15:21.484131","created_date":"2021-09-27T00:00:00"}