{"id":"https://openalex.org/W4312929132","doi":"https://doi.org/10.1109/lsp.2022.3214155","title":"Text Enhancement Network for Cross-Domain Scene Text Detection","display_name":"Text Enhancement Network for Cross-Domain Scene Text Detection","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312929132","doi":"https://doi.org/10.1109/lsp.2022.3214155"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2022.3214155","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2022.3214155","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-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/A5007294024","display_name":"Jinhong Deng","orcid":"https://orcid.org/0000-0003-0939-0669"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinhong Deng","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0003-0939-0669","affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083043553","display_name":"Xiulian Luo","orcid":"https://orcid.org/0000-0001-7537-2202"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiulian Luo","raw_affiliation_strings":["Science and Technology on Electronic Information Control Laboratory, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Science and Technology on Electronic Information Control Laboratory, Chengdu, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110029573","display_name":"Jiawen Zheng","orcid":"https://orcid.org/0009-0002-3824-8055"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiawen Zheng","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028258004","display_name":"Wanli Dang","orcid":"https://orcid.org/0000-0002-9108-737X"},"institutions":[{"id":"https://openalex.org/I1299457549","display_name":"Civil Aviation Administration of China","ror":"https://ror.org/05gfwht30","country_code":"CN","type":"government","lineage":["https://openalex.org/I1299457549","https://openalex.org/I4210127216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wanli Dang","raw_affiliation_strings":["Second Research Institute of the Civil Aviation Administration of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-9108-737X","affiliations":[{"raw_affiliation_string":"Second Research Institute of the Civil Aviation Administration of China, Chengdu, China","institution_ids":["https://openalex.org/I1299457549"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100719271","display_name":"Wen Li","orcid":"https://orcid.org/0000-0002-5559-8594"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wen Li","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-5559-8594","affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5873,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.67094886,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"29","issue":null,"first_page":"2203","last_page":"2207"},"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/T12707","display_name":"Vehicle License Plate Recognition","score":0.9919999837875366,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.977400004863739,"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":0.8179471492767334},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.71614009141922},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6702091693878174},{"id":"https://openalex.org/keywords/text-detection","display_name":"Text detection","score":0.5448569655418396},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.5164380669593811},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4918217658996582},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.479882150888443},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4585518538951874},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.44639620184898376},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.43885916471481323},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43829044699668884},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4290873110294342},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3804788291454315},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3268536627292633}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8179471492767334},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.71614009141922},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6702091693878174},{"id":"https://openalex.org/C2983589003","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Text detection","level":3,"score":0.5448569655418396},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.5164380669593811},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4918217658996582},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.479882150888443},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4585518538951874},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.44639620184898376},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.43885916471481323},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43829044699668884},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4290873110294342},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3804788291454315},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3268536627292633},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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":"doi:10.1109/lsp.2022.3214155","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2022.3214155","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1081440678","display_name":null,"funder_award_id":"62176047","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2042749131","display_name":null,"funder_award_id":"ZYGX2021YGLH208","funder_id":"https://openalex.org/F4320323292","funder_display_name":"University of Electronic Science and Technology of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323292","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1731081199","https://openalex.org/W1882958252","https://openalex.org/W1972065312","https://openalex.org/W2008806374","https://openalex.org/W2144554289","https://openalex.org/W2194775991","https://openalex.org/W2343052201","https://openalex.org/W2605982830","https://openalex.org/W2767009334","https://openalex.org/W2873558679","https://openalex.org/W2921478860","https://openalex.org/W2925281733","https://openalex.org/W2950111065","https://openalex.org/W2955889502","https://openalex.org/W2962914239","https://openalex.org/W2963073217","https://openalex.org/W2964115968","https://openalex.org/W2968634921","https://openalex.org/W2969893028","https://openalex.org/W2985406498","https://openalex.org/W2987563462","https://openalex.org/W2990069979","https://openalex.org/W2991699366","https://openalex.org/W3022121429","https://openalex.org/W3034779842","https://openalex.org/W3046641203","https://openalex.org/W3099562471","https://openalex.org/W3106723659","https://openalex.org/W3106879600","https://openalex.org/W3166409449","https://openalex.org/W3202115483","https://openalex.org/W3209366795","https://openalex.org/W4212991279","https://openalex.org/W4213232147","https://openalex.org/W4225683503","https://openalex.org/W4312473311","https://openalex.org/W4312988011","https://openalex.org/W4312993742","https://openalex.org/W4313160574","https://openalex.org/W6637618735","https://openalex.org/W6639480849","https://openalex.org/W6642972425"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W4246396837","https://openalex.org/W3176240006","https://openalex.org/W3126451824","https://openalex.org/W2482350142","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4288019534","https://openalex.org/W3011293149"],"abstract_inverted_index":{"Conventional":[0],"scene":[1,24,75],"text":[2,25,76,118],"detection":[3],"approaches":[4],"essentially":[5],"assume":[6],"that":[7,45],"training":[8,40],"and":[9,18,95,120,156],"test":[10,47],"data":[11,97],"are":[12],"drawn":[13],"from":[14,29,44,50,98],"the":[15,36,56,93,107,115,123,130,144,157,161],"same":[16],"distribution":[17,38],"have":[19],"achieved":[20],"compelling":[21],"results.":[22],"However,":[23],"detectors":[26],"often":[27],"suffer":[28],"performance":[30,145],"degradation":[31],"in":[32,126],"real-world":[33],"applications,":[34],"since":[35],"feature":[37],"of":[39,46,92,117,146,163],"images":[41,48],"is":[42],"different":[43],"obtained":[49],"a":[51,61,82,138],"new":[52],"scene.":[53],"To":[54],"address":[55],"above":[57],"problems,":[58],"we":[59,79,105,136],"propose":[60],"novel":[62],"method":[63],"called":[64],"Text":[65,108],"Enhancement":[66,110],"Network":[67],"(TEN)":[68],"based":[69],"on":[70,153],"adversarial":[71],"learning":[72],"for":[73],"cross-domain":[74],"detection.":[77],"Specifically,":[78],"first":[80],"design":[81,137],"Multi-adversarial":[83],"Feature":[84],"Alignment":[85],"(MFA)":[86],"module":[87,112],"to":[88,101,113,128,141],"maximally":[89],"align":[90],"features":[91],"source":[94],"target":[96],"low-level":[99],"texture":[100],"high-level":[102],"semantics.":[103],"Second,":[104],"develop":[106],"Attention":[109],"(TAE)":[111],"re-weigh":[114],"importance":[116],"regions":[119],"accordingly":[121],"enhance":[122],"corresponding":[124],"features,":[125],"order":[127],"improve":[129],"robustness":[131],"against":[132],"noisy":[133],"background.":[134],"Additionally,":[135],"self-training":[139],"strategy":[140],"further":[142],"boost":[143],"our":[147,164],"TEN.":[148,165],"We":[149],"conduct":[150],"extensive":[151],"experiments":[152],"five":[154],"benchmarks,":[155],"experimental":[158],"results":[159],"demonstrate":[160],"effectiveness":[162]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
