{"id":"https://openalex.org/W3010428518","doi":"https://doi.org/10.1109/wacv45572.2020.9093544","title":"Erasing Scene Text with Weak Supervision","display_name":"Erasing Scene Text with Weak Supervision","publication_year":2020,"publication_date":"2020-03-01","ids":{"openalex":"https://openalex.org/W3010428518","doi":"https://doi.org/10.1109/wacv45572.2020.9093544","mag":"3010428518"},"language":"en","primary_location":{"id":"doi:10.1109/wacv45572.2020.9093544","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093544","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","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/A5004224952","display_name":"Jan Zdenek","orcid":"https://orcid.org/0009-0000-9761-8672"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Jan Zdenek","raw_affiliation_strings":["The University of Tokyo"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050229964","display_name":"Hideki Nakayama","orcid":"https://orcid.org/0000-0001-8726-2780"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hideki Nakayama","raw_affiliation_strings":["The University of Tokyo"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5004224952"],"corresponding_institution_ids":["https://openalex.org/I74801974"],"apc_list":null,"apc_paid":null,"fwci":1.5632,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.85144854,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2227","last_page":"2235"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9975000023841858,"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":0.9901000261306763,"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/inpainting","display_name":"Inpainting","score":0.8908634185791016},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7512878179550171},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7190319299697876},{"id":"https://openalex.org/keywords/text-detection","display_name":"Text detection","score":0.6330611705780029},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.622975766658783},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.6192848682403564},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5904093384742737},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5067732930183411},{"id":"https://openalex.org/keywords/license","display_name":"License","score":0.4729727804660797},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.4606187045574188},{"id":"https://openalex.org/keywords/natural","display_name":"Natural (archaeology)","score":0.4559304416179657},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4502696990966797},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4265051782131195},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3577447831630707},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.35536953806877136},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.09858366847038269},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08270701766014099}],"concepts":[{"id":"https://openalex.org/C11727466","wikidata":"https://www.wikidata.org/wiki/Q1628157","display_name":"Inpainting","level":3,"score":0.8908634185791016},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7512878179550171},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7190319299697876},{"id":"https://openalex.org/C2983589003","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Text detection","level":3,"score":0.6330611705780029},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.622975766658783},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.6192848682403564},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5904093384742737},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5067732930183411},{"id":"https://openalex.org/C2780560020","wikidata":"https://www.wikidata.org/wiki/Q79719","display_name":"License","level":2,"score":0.4729727804660797},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.4606187045574188},{"id":"https://openalex.org/C2776608160","wikidata":"https://www.wikidata.org/wiki/Q4785462","display_name":"Natural (archaeology)","level":2,"score":0.4559304416179657},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4502696990966797},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4265051782131195},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3577447831630707},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.35536953806877136},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.09858366847038269},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08270701766014099},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wacv45572.2020.9093544","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093544","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.5699999928474426,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W117491841","https://openalex.org/W1901129140","https://openalex.org/W1976597276","https://openalex.org/W1993120651","https://openalex.org/W1998042868","https://openalex.org/W2008806374","https://openalex.org/W2061802763","https://openalex.org/W2082269761","https://openalex.org/W2099471712","https://openalex.org/W2100415658","https://openalex.org/W2117539524","https://openalex.org/W2142159465","https://openalex.org/W2144554289","https://openalex.org/W2160197540","https://openalex.org/W2194775991","https://openalex.org/W2239285313","https://openalex.org/W2295936755","https://openalex.org/W2331128040","https://openalex.org/W2343052201","https://openalex.org/W2580458810","https://openalex.org/W2593539516","https://openalex.org/W2605982830","https://openalex.org/W2612775908","https://openalex.org/W2725486421","https://openalex.org/W2732026016","https://openalex.org/W2738588019","https://openalex.org/W2784050770","https://openalex.org/W2785383245","https://openalex.org/W2798365772","https://openalex.org/W2875814315","https://openalex.org/W2903311229","https://openalex.org/W2962793481","https://openalex.org/W2963005009","https://openalex.org/W2963017889","https://openalex.org/W2963073614","https://openalex.org/W2963150697","https://openalex.org/W2963255313","https://openalex.org/W2963398399","https://openalex.org/W2963420272","https://openalex.org/W2963502975","https://openalex.org/W2963647456","https://openalex.org/W2963977642","https://openalex.org/W2964018263","https://openalex.org/W2982763192","https://openalex.org/W3003433862","https://openalex.org/W3024377038","https://openalex.org/W3102695566","https://openalex.org/W3106228955","https://openalex.org/W4249710618","https://openalex.org/W4320013936","https://openalex.org/W6639824700","https://openalex.org/W6649973027","https://openalex.org/W6702130928","https://openalex.org/W6732779862","https://openalex.org/W6739844568","https://openalex.org/W6740934225","https://openalex.org/W6750997056","https://openalex.org/W6752670383","https://openalex.org/W6756127406","https://openalex.org/W6756921968"],"related_works":["https://openalex.org/W2380775572","https://openalex.org/W2213520135","https://openalex.org/W4242046654","https://openalex.org/W1504109132","https://openalex.org/W3174923100","https://openalex.org/W3134074939","https://openalex.org/W2117562399","https://openalex.org/W2244018504","https://openalex.org/W4298074124","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Scene":[0],"text":[1,8,51,74,80,100,108,114,154,170],"erasing":[2,52],"is":[3,24,155,165],"a":[4,47,58,96,132,147],"task":[5],"of":[6,70,113],"removing":[7],"from":[9,77],"natural":[10],"scene":[11,50,99,107],"images,":[12],"which":[13,67,78,116,151],"has":[14,81],"been":[15,82],"gaining":[16],"attention":[17],"in":[18,40,137,141,150,173],"recent":[19],"years.":[20],"The":[21,106,126,159],"main":[22],"motivation":[23],"to":[25,64,167,177],"conceal":[26],"private":[27],"information":[28],"such":[29],"as":[30,57,120],"license":[31],"plate":[32],"numbers,":[33],"and":[34,75,102,145,171],"house":[35],"nameplates":[36],"that":[37,53,162],"can":[38],"appear":[39],"images.":[41,180],"In":[42,62],"this":[43],"work,":[44],"we":[45],"propose":[46],"method":[48,85,164],"for":[49,92,122,128],"approaches":[54],"the":[55,79,123,152,174],"problem":[56],"general":[59],"inpainting":[60,104,124],"task.":[61],"contrast":[63],"previous":[65],"methods,":[66],"require":[68],"pairs":[69,91],"original":[71,153],"images":[72,76],"containing":[73],"removed,":[83],"our":[84,163],"does":[86],"not":[87],"need":[88],"corresponding":[89],"image":[90,134,144,149],"training.":[93],"We":[94],"use":[95],"separately":[97],"trained":[98,130],"detector":[101,109],"an":[103,142],"network.":[105,125],"predicts":[110],"segmentation":[111],"maps":[112],"instances":[115],"are":[117],"then":[118],"used":[119],"masks":[121],"network":[127],"inpainting,":[129],"on":[131],"large-scale":[133],"dataset,":[135],"fills":[136],"masked":[138],"out":[139],"regions":[140],"input":[143],"generates":[146],"final":[148],"no":[156],"longer":[157],"present.":[158],"results":[160],"show":[161],"able":[166],"successfully":[168],"remove":[169],"fill":[172],"created":[175],"holes":[176],"produce":[178],"natural-looking":[179]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}