{"id":"https://openalex.org/W2964018263","doi":"https://doi.org/10.1109/cvpr.2018.00595","title":"FOTS: Fast Oriented Text Spotting with a Unified Network","display_name":"FOTS: Fast Oriented Text Spotting with a Unified Network","publication_year":2018,"publication_date":"2018-06-01","ids":{"openalex":"https://openalex.org/W2964018263","doi":"https://doi.org/10.1109/cvpr.2018.00595","mag":"2964018263"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2018.00595","doi":"https://doi.org/10.1109/cvpr.2018.00595","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2018.00595","pdf_url":null,"source":{"id":"https://openalex.org/S4210176548","display_name":"IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings","issn_l":"1063-6919","issn":["1063-6919","2332-564X","2575-7075"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-1"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1801.01671","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101599729","display_name":"Xuebo Liu","orcid":"https://orcid.org/0000-0001-8524-2006","observed_orcids":["https://orcid.org/0000-0001-8524-2006"]},"institutions":[{"id":"https://openalex.org/I4401727009","display_name":"Sensetime (China)","ror":"https://ror.org/049wsmj07","country_code":"CN","type":"company","lineage":["https://openalex.org/I4401727009"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuebo Liu","raw_affiliation_strings":["SenseTime Group Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SenseTime Group Ltd","institution_ids":["https://openalex.org/I4401727009"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100751872","display_name":"Ding Liang","orcid":"https://orcid.org/0000-0001-9774-4687","observed_orcids":["https://orcid.org/0000-0001-9774-4687"]},"institutions":[{"id":"https://openalex.org/I4401727009","display_name":"Sensetime (China)","ror":"https://ror.org/049wsmj07","country_code":"CN","type":"company","lineage":["https://openalex.org/I4401727009"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ding Liang","raw_affiliation_strings":["SenseTime Group Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SenseTime Group Ltd","institution_ids":["https://openalex.org/I4401727009"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101411504","display_name":"Shi Yan","orcid":"https://orcid.org/0000-0002-4396-0488","observed_orcids":["https://orcid.org/0000-0002-4396-0488"]},"institutions":[{"id":"https://openalex.org/I4401727009","display_name":"Sensetime (China)","ror":"https://ror.org/049wsmj07","country_code":"CN","type":"company","lineage":["https://openalex.org/I4401727009"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shi Yan","raw_affiliation_strings":["SenseTime Group Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SenseTime Group Ltd","institution_ids":["https://openalex.org/I4401727009"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103019021","display_name":"Dagui Chen","orcid":"https://orcid.org/0000-0003-0850-8231","observed_orcids":["https://orcid.org/0000-0003-0850-8231"]},"institutions":[{"id":"https://openalex.org/I4401727009","display_name":"Sensetime (China)","ror":"https://ror.org/049wsmj07","country_code":"CN","type":"company","lineage":["https://openalex.org/I4401727009"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dagui Chen","raw_affiliation_strings":["SenseTime Group Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SenseTime Group Ltd","institution_ids":["https://openalex.org/I4401727009"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100748135","display_name":"Yu Qiao","orcid":"https://orcid.org/0000-0002-1889-2567","observed_orcids":["https://orcid.org/0000-0002-1889-2567","https://orcid.org/0000-0003-4045-8473"]},"institutions":[{"id":"https://openalex.org/I4401727009","display_name":"Sensetime (China)","ror":"https://ror.org/049wsmj07","country_code":"CN","type":"company","lineage":["https://openalex.org/I4401727009"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Qiao","raw_affiliation_strings":["SenseTime Group Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SenseTime Group Ltd","institution_ids":["https://openalex.org/I4401727009"]}]},{"author_position":"last","author":{"id":null,"display_name":"Junjie Yan","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4401727009","display_name":"Sensetime (China)","ror":"https://ror.org/049wsmj07","country_code":"CN","type":"company","lineage":["https://openalex.org/I4401727009"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junjie Yan","raw_affiliation_strings":["SenseTime Group Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SenseTime Group Ltd","institution_ids":["https://openalex.org/I4401727009"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4401727009"],"apc_list":null,"apc_paid":null,"fwci":21.9735,"has_fulltext":true,"cited_by_count":557,"citation_normalized_percentile":{"value":0.99406561,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"5676","last_page":"5685"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":1.0,"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":1.0,"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/T12707","display_name":"Vehicle License Plate Recognition","score":9.999999747378752e-05,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.0,"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/scene-text-detection","display_name":"scene text detection","score":0.7490000128746033},{"id":"https://openalex.org/keywords/scene-text-recognition","display_name":"scene text recognition","score":0.8870000243186951},{"id":"https://openalex.org/keywords/document-analysis","display_name":"document analysis","score":0.5450000166893005}],"concepts":[{"id":"https://openalex.org/C2779506182","wikidata":"https://www.wikidata.org/wiki/Q7580141","display_name":"Spotting","level":2,"score":0.9580807685852051},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8363019227981567},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6246862411499023},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5677730441093445},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5601309537887573},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5214197635650635},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4923034906387329},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4345772862434387},{"id":"https://openalex.org/C2983589003","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Text detection","level":3,"score":0.4126778542995453},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.14710375666618347},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.13628217577934265},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.08443105220794678},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/cvpr.2018.00595","doi":"https://doi.org/10.1109/cvpr.2018.00595","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2018.00595","pdf_url":null,"source":{"id":"https://openalex.org/S4210176548","display_name":"IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings","issn_l":"1063-6919","issn":["1063-6919","2332-564X","2575-7075"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-1"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1801.01671","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1801.01671","pdf_url":"https://arxiv.org/pdf/1801.01671","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,"listed_in":[],"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"},{"id":"doi:10.48550/arxiv.1801.01671","doi":"https://doi.org/10.48550/arxiv.1801.01671","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1801.01671","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,"listed_in":[],"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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1801.01671","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1801.01671","pdf_url":"https://arxiv.org/pdf/1801.01671","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,"listed_in":[],"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":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2964018263.pdf","grobid_xml":"https://content.openalex.org/works/W2964018263.grobid-xml"},"referenced_works_count":64,"referenced_works":["https://openalex.org/W70975097","https://openalex.org/W603908379","https://openalex.org/W639708223","https://openalex.org/W1491389626","https://openalex.org/W1536680647","https://openalex.org/W1686810756","https://openalex.org/W1827297289","https://openalex.org/W1902237438","https://openalex.org/W1922126009","https://openalex.org/W2008806374","https://openalex.org/W2019478948","https://openalex.org/W2043075591","https://openalex.org/W2056435187","https://openalex.org/W2064675550","https://openalex.org/W2127141656","https://openalex.org/W2128854450","https://openalex.org/W2131673214","https://openalex.org/W2131774270","https://openalex.org/W2137718414","https://openalex.org/W2140132917","https://openalex.org/W2144554289","https://openalex.org/W2148214126","https://openalex.org/W2153182373","https://openalex.org/W2155893237","https://openalex.org/W2163605009","https://openalex.org/W2194187530","https://openalex.org/W2194775991","https://openalex.org/W2204328893","https://openalex.org/W2279655419","https://openalex.org/W2294053032","https://openalex.org/W2341497066","https://openalex.org/W2343052201","https://openalex.org/W2472159136","https://openalex.org/W2504335775","https://openalex.org/W2519818067","https://openalex.org/W2550687635","https://openalex.org/W2565639579","https://openalex.org/W2593539516","https://openalex.org/W2593572697","https://openalex.org/W2604735854","https://openalex.org/W2605076167","https://openalex.org/W2605982830","https://openalex.org/W2725486421","https://openalex.org/W2749330229","https://openalex.org/W2806070179","https://openalex.org/W2949335953","https://openalex.org/W2949533892","https://openalex.org/W2949650786","https://openalex.org/W2951005624","https://openalex.org/W2951548327","https://openalex.org/W2952302849","https://openalex.org/W2952439627","https://openalex.org/W2962790387","https://openalex.org/W2962804639","https://openalex.org/W2962984063","https://openalex.org/W2963150697","https://openalex.org/W2963187132","https://openalex.org/W2963517393","https://openalex.org/W2963977642","https://openalex.org/W2964057904","https://openalex.org/W2964296749","https://openalex.org/W3106250896","https://openalex.org/W6739844568","https://openalex.org/W7098642242"],"related_works":["https://openalex.org/W3134513473","https://openalex.org/W3016205750","https://openalex.org/W2962986948","https://openalex.org/W2784050770","https://openalex.org/W3003552100","https://openalex.org/W2860641358","https://openalex.org/W4225683503","https://openalex.org/W2790704751","https://openalex.org/W4386160384","https://openalex.org/W3179426054"],"abstract_inverted_index":{"Incidental":[0],"scene":[1],"text":[2,23,86,133,149],"spotting":[3,134,150],"is":[4,62],"considered":[5],"one":[6],"of":[7],"the":[8,15,56,90,116,129],"most":[9],"difficult":[10],"and":[11,25,48,52,70,89,110],"valuable":[12],"challenges":[13],"in":[14],"document":[16],"analysis":[17],"community.":[18],"Most":[19],"existing":[20],"methods":[21,121],"treat":[22],"detection":[24,47,69,87],"recognition":[26],"as":[27],"separate":[28],"tasks.":[29,59],"In":[30],"this":[31],"work,":[32],"we":[33],"propose":[34],"a":[35],"unified":[36],"end-to-end":[37],"trainable":[38],"Fast":[39],"Oriented":[40],"Text":[41],"Spotting":[42],"(FOTS)":[43],"network":[44],"for":[45],"simultaneous":[46],"recognition,":[49],"sharing":[50,75],"computation":[51,81],"visual":[53],"information":[54],"among":[55],"two":[57],"complementary":[58],"Specifically,":[60],"RoIRotate":[61],"introduced":[63],"to":[64,84,127],"share":[65],"convolutional":[66],"features":[67],"between":[68],"recognition.":[71],"Benefiting":[72],"from":[73],"convolution":[74],"strategy,":[76],"our":[77,95],"FOTS":[78],"has":[79],"little":[80],"overhead":[82],"compared":[83],"baseline":[85],"network,":[88],"joint":[91],"training":[92],"method":[93,96,118],"makes":[94],"perform":[97],"better":[98],"than":[99,144],"these":[100],"two-stage":[101],"methods.":[102],"Experiments":[103],"on":[104,146],"ICDAR":[105,107,111,147],"2015,":[106],"2017":[108],"MLT,":[109],"2013":[112],"datasets":[113],"demonstrate":[114],"that":[115],"proposed":[117],"outperforms":[119],"state-of-the-art":[120,140],"significantly,":[122],"which":[123,136],"further":[124],"allows":[125],"us":[126],"develop":[128],"first":[130],"real-time":[131],"oriented":[132],"system":[135],"surpasses":[137],"all":[138],"previous":[139],"results":[141],"by":[142],"more":[143],"5%":[145],"2015":[148],"task":[151],"while":[152],"keeping":[153],"22.6":[154],"fps.":[155]},"counts_by_year":[{"year":2026,"cited_by_count":17},{"year":2025,"cited_by_count":38},{"year":2024,"cited_by_count":57},{"year":2023,"cited_by_count":59},{"year":2022,"cited_by_count":85},{"year":2021,"cited_by_count":108},{"year":2020,"cited_by_count":103},{"year":2019,"cited_by_count":77},{"year":2018,"cited_by_count":13}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2019-07-30T00:00:00"}