{"id":"https://openalex.org/W2891451370","doi":"https://doi.org/10.1109/icip.2018.8451402","title":"Feature Fusion Network for Scene Text Detection","display_name":"Feature Fusion Network for Scene Text Detection","publication_year":2018,"publication_date":"2018-09-07","ids":{"openalex":"https://openalex.org/W2891451370","doi":"https://doi.org/10.1109/icip.2018.8451402","mag":"2891451370"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2018.8451402","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2018.8451402","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5085472971","display_name":"Chenqin Cai","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenqin Cai","raw_affiliation_strings":["University of Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041894655","display_name":"Pin Lv","orcid":"https://orcid.org/0000-0002-3425-9913"},"institutions":[{"id":"https://openalex.org/I4210128818","display_name":"Institute of Software","ror":"https://ror.org/033dfsn42","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128818"]},{"id":"https://openalex.org/I84653119","display_name":"Academia Sinica","ror":"https://ror.org/05bxb3784","country_code":"TW","type":"facility","lineage":["https://openalex.org/I84653119"]}],"countries":["CN","TW"],"is_corresponding":false,"raw_author_name":"Pin Lv","raw_affiliation_strings":["Institute of Software Chinese Academy of Sciences(ISCAS)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Software Chinese Academy of Sciences(ISCAS)","institution_ids":["https://openalex.org/I4210128818","https://openalex.org/I84653119"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027552992","display_name":"Bing Su","orcid":"https://orcid.org/0000-0001-8560-1910"},"institutions":[{"id":"https://openalex.org/I4210128818","display_name":"Institute of Software","ror":"https://ror.org/033dfsn42","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128818"]},{"id":"https://openalex.org/I84653119","display_name":"Academia Sinica","ror":"https://ror.org/05bxb3784","country_code":"TW","type":"facility","lineage":["https://openalex.org/I84653119"]}],"countries":["CN","TW"],"is_corresponding":false,"raw_author_name":"Bing Su","raw_affiliation_strings":["Institute of Software Chinese Academy of Sciences(ISCAS)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Software Chinese Academy of Sciences(ISCAS)","institution_ids":["https://openalex.org/I4210128818","https://openalex.org/I84653119"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2755","last_page":"2759"},"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":0.9872999787330627,"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":0.9825000166893005,"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":0.7956587076187134},{"id":"https://openalex.org/keywords/text-detection","display_name":"Text detection","score":0.7714303731918335},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7340917587280273},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6248970627784729},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6226674914360046},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5982670187950134},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5708374381065369},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.5523003339767456},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.5194537043571472},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5124890804290771},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.49306270480155945},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3886878490447998},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3549962639808655}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7956587076187134},{"id":"https://openalex.org/C2983589003","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Text detection","level":3,"score":0.7714303731918335},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7340917587280273},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6248970627784729},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6226674914360046},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5982670187950134},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5708374381065369},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.5523003339767456},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.5194537043571472},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5124890804290771},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.49306270480155945},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3886878490447998},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3549962639808655},{"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},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2018.8451402","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2018.8451402","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W117491841","https://openalex.org/W639708223","https://openalex.org/W1533861849","https://openalex.org/W1935817682","https://openalex.org/W2008806374","https://openalex.org/W2061802763","https://openalex.org/W2111886867","https://openalex.org/W2117539524","https://openalex.org/W2128854450","https://openalex.org/W2150259535","https://openalex.org/W2155893237","https://openalex.org/W2194775991","https://openalex.org/W2239285313","https://openalex.org/W2253806798","https://openalex.org/W2322480645","https://openalex.org/W2395360388","https://openalex.org/W2464918637","https://openalex.org/W2511730936","https://openalex.org/W2519818067","https://openalex.org/W2550687635","https://openalex.org/W2579985080","https://openalex.org/W2587376528","https://openalex.org/W2605982830","https://openalex.org/W2613718673","https://openalex.org/W2617708032","https://openalex.org/W2750933790","https://openalex.org/W2950094539","https://openalex.org/W2963058975","https://openalex.org/W2963446712","https://openalex.org/W2963813458","https://openalex.org/W2963977642","https://openalex.org/W3106250896","https://openalex.org/W4295246343","https://openalex.org/W6620707391","https://openalex.org/W6631943919","https://openalex.org/W6679238701","https://openalex.org/W6689736890","https://openalex.org/W6712036928","https://openalex.org/W6726857151"],"related_works":["https://openalex.org/W2366906938","https://openalex.org/W2349391998","https://openalex.org/W4205655149","https://openalex.org/W2000775715","https://openalex.org/W2074467390","https://openalex.org/W2795393339","https://openalex.org/W2626393719","https://openalex.org/W4390618967","https://openalex.org/W2174745845","https://openalex.org/W3011293149"],"abstract_inverted_index":{"Detecting":[0],"scene":[1,80,117],"text":[2,13,22,37,63,81,118,123],"in":[3,41],"natural":[4],"images":[5],"is":[6,32],"a":[7,28,50,97,129],"challenging":[8],"task":[9],"due":[10,75],"to":[11,54,61,76,105,107],"various":[12,40,126],"scales,":[14],"uneven":[15],"lighting,":[16],"burring":[17],"and":[18,57,82,139],"perspective":[19],"distortion.":[20],"Retrospectively,":[21],"detection":[23],"features":[24,60],"are":[25,39],"extracted":[26],"from":[27],"single":[29],"scale":[30],"which":[31,120],"not":[33],"sufficient":[34],"enough":[35],"since":[36],"regions":[38,64,124],"enormous":[42],"sizes.":[43],"To":[44],"address":[45],"the":[46,77,101],"issue,":[47],"we":[48,93],"design":[49],"Feature":[51],"Fusion":[52],"Network":[53],"concatenate":[55],"lower":[56],"higher":[58],"level":[59],"detect":[62,122],"of":[65,125],"multiple":[66],"scales.":[67],"Besides,":[68],"as":[69,96],"it":[70],"may":[71],"incur":[72],"learning":[73],"bias":[74],"difference":[78],"between":[79],"general":[83,90],"object":[84,91],"when":[85],"using":[86],"models":[87],"pre-trained":[88,130],"on":[89,136],"datasets,":[92],"extend":[94],"DenseNet":[95],"base":[98],"network":[99],"during":[100],"feature":[102],"extraction":[103],"stage":[104],"help":[106],"start":[108],"training":[109],"without":[110,128],"pre-training.":[111],"Our":[112],"model":[113],"enables":[114],"an":[115],"end-to-end":[116],"detector":[119],"can":[121],"scales":[127],"model.":[131],"It":[132],"achieves":[133],"state-of-the-art":[134],"results":[135],"ICDAR":[137],"2013":[138],"COCO-Text":[140],"benchmarks.":[141]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":4}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
