{"id":"https://openalex.org/W3161557873","doi":"https://doi.org/10.1109/icpr48806.2021.9412223","title":"TCATD: Text Contour Attention for Scene Text Detection","display_name":"TCATD: Text Contour Attention for Scene Text Detection","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3161557873","doi":"https://doi.org/10.1109/icpr48806.2021.9412223","mag":"3161557873"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9412223","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412223","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/A5004129019","display_name":"Ziling Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"ZiLing Hu","raw_affiliation_strings":["East China Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043728985","display_name":"Xingjiao Wu","orcid":"https://orcid.org/0000-0001-9146-051X"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingiiao Wu","raw_affiliation_strings":["East China Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100704230","display_name":"Jing Yang","orcid":"https://orcid.org/0000-0002-6407-1276"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Yang","raw_affiliation_strings":["East China Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":0.8733,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.75328947,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1083","last_page":"1088"},"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":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9933000206947327,"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":0.7027822732925415},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6822502613067627},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5891324281692505},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5352720618247986},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5124247670173645},{"id":"https://openalex.org/keywords/text-detection","display_name":"Text detection","score":0.5006844997406006},{"id":"https://openalex.org/keywords/text-segmentation","display_name":"Text segmentation","score":0.48604875802993774},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.47906574606895447},{"id":"https://openalex.org/keywords/text-recognition","display_name":"Text recognition","score":0.47279757261276245},{"id":"https://openalex.org/keywords/active-contour-model","display_name":"Active contour model","score":0.4632253646850586},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4551744759082794},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42930787801742554},{"id":"https://openalex.org/keywords/orientation","display_name":"Orientation (vector space)","score":0.4183810353279114},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.37917229533195496},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.23347672820091248},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.10843366384506226},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10131099820137024},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09276571869850159}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7027822732925415},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6822502613067627},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5891324281692505},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5352720618247986},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5124247670173645},{"id":"https://openalex.org/C2983589003","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Text detection","level":3,"score":0.5006844997406006},{"id":"https://openalex.org/C98501671","wikidata":"https://www.wikidata.org/wiki/Q1948408","display_name":"Text segmentation","level":3,"score":0.48604875802993774},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.47906574606895447},{"id":"https://openalex.org/C2983812711","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Text recognition","level":3,"score":0.47279757261276245},{"id":"https://openalex.org/C112353826","wikidata":"https://www.wikidata.org/wiki/Q127313","display_name":"Active contour model","level":4,"score":0.4632253646850586},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4551744759082794},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42930787801742554},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.4183810353279114},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.37917229533195496},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.23347672820091248},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.10843366384506226},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10131099820137024},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09276571869850159},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr48806.2021.9412223","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412223","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":[],"awards":[{"id":"https://openalex.org/G3013163701","display_name":null,"funder_award_id":"18511103105","funder_id":"https://openalex.org/F4320321885","funder_display_name":"Science and Technology Commission of Shanghai Municipality"}],"funders":[{"id":"https://openalex.org/F4320321885","display_name":"Science and Technology Commission of Shanghai Municipality","ror":"https://ror.org/03kt66j61"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1903029394","https://openalex.org/W2076014259","https://openalex.org/W2128854450","https://openalex.org/W2194775991","https://openalex.org/W2263734677","https://openalex.org/W2300687442","https://openalex.org/W2339589954","https://openalex.org/W2560622558","https://openalex.org/W2565639579","https://openalex.org/W2593539516","https://openalex.org/W2605076167","https://openalex.org/W2605982830","https://openalex.org/W2613718673","https://openalex.org/W2766895242","https://openalex.org/W2772800855","https://openalex.org/W2776766448","https://openalex.org/W2785383245","https://openalex.org/W2786480153","https://openalex.org/W2810028092","https://openalex.org/W2902494497","https://openalex.org/W2953894958","https://openalex.org/W2962810613","https://openalex.org/W2963299604","https://openalex.org/W2963353821","https://openalex.org/W2963647456","https://openalex.org/W2963840241","https://openalex.org/W2963977642","https://openalex.org/W2963996347","https://openalex.org/W2964294787","https://openalex.org/W2964685115","https://openalex.org/W2967155990","https://openalex.org/W2967615747","https://openalex.org/W3024377038","https://openalex.org/W3101769104","https://openalex.org/W3106228955","https://openalex.org/W3106250896","https://openalex.org/W4241071816","https://openalex.org/W6620707391","https://openalex.org/W6748033758","https://openalex.org/W6748140492","https://openalex.org/W6752143097","https://openalex.org/W6756921968","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W4312663241","https://openalex.org/W4221004363","https://openalex.org/W2885157826","https://openalex.org/W2159463658","https://openalex.org/W2963299604","https://openalex.org/W4388208420","https://openalex.org/W3211262047","https://openalex.org/W950386562","https://openalex.org/W2363517123","https://openalex.org/W3104052051"],"abstract_inverted_index":{"Segmentation-based":[0],"approaches":[1],"have":[2],"enabled":[3],"state-of-the-art":[4,145],"performance":[5],"in":[6,33],"long":[7],"or":[8],"curved":[9],"text":[10,22,49,63,67,73,81,92,103],"detection":[11,15],"tasks.":[12],"However,":[13],"false":[14],"still":[16],"is":[17],"a":[18,38,108],"challenge":[19],"when":[20],"two":[21],"instances":[23],"are":[24],"close":[25],"to":[26,88,113],"each":[27],"other.":[28],"To":[29],"address":[30],"this":[31,34],"problem,":[32],"paper,":[35],"we":[36,106],"propose":[37,107],"Text":[39,42,109,120],"Contour":[40,110,121],"Attention":[41,111,122],"Detector":[43],"(TCATD),":[44],"which":[45],"can":[46,79,86,97],"locate":[47],"scene":[48],"with":[50,115],"arbitrary":[51],"orientation":[52],"and":[53,72,94,126,136],"shape":[54,101],"accurately.":[55],"Different":[56],"from":[57],"previous":[58],"work,":[59],"TCATD":[60],"focus":[61],"on":[62,133],"contour":[64,82,116],"map":[65,70],"(TC),":[66],"center":[68],"intensity":[69],"(TCI)":[71],"kernel":[74],"maps":[75],"(TK).":[76],"The":[77],"TC":[78],"introduce":[80],"information,":[83],"the":[84,90,95,99,119,140,144],"TCI":[85,125],"help":[87],"learn":[89],"accurate":[91],"segmentation":[93],"TK":[96,127],"generate":[98],"complete":[100],"of":[102],"instances.":[104],"Besides,":[105],"Module":[112],"deal":[114],"information.":[117],"After":[118],"Module,":[123],"TC,":[124],"will":[128],"be":[129],"obtained.":[130],"Extensive":[131],"experiments":[132],"ICDAR2015,":[134],"CTW1500":[135],"Total-Text":[137],"demonstrate":[138],"that":[139],"proposed":[141],"method":[142],"achieves":[143],"performance.":[146]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
