{"id":"https://openalex.org/W3085394167","doi":"https://doi.org/10.1109/access.2020.3023782","title":"Face Detection Based on Receptive Field Enhanced Multi-Task Cascaded Convolutional Neural Networks","display_name":"Face Detection Based on Receptive Field Enhanced Multi-Task Cascaded Convolutional Neural Networks","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3085394167","doi":"https://doi.org/10.1109/access.2020.3023782","mag":"3085394167"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3023782","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3023782","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09195457.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09195457.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063940644","display_name":"Xiaochao Li","orcid":"https://orcid.org/0000-0001-7469-7064"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]},{"id":"https://openalex.org/I4210134189","display_name":"Xiamen University Malaysia","ror":"https://ror.org/0331wa828","country_code":"MY","type":"education","lineage":["https://openalex.org/I191208505","https://openalex.org/I4210134189"]}],"countries":["CN","MY"],"is_corresponding":false,"raw_author_name":"Xiaochao Li","raw_affiliation_strings":["Xiamen University Malaysia, Sepang, Malaysia","Xiamen University, Xiamen, China"],"raw_orcid":"https://orcid.org/0000-0001-7469-7064","affiliations":[{"raw_affiliation_string":"Xiamen University Malaysia, Sepang, Malaysia","institution_ids":["https://openalex.org/I4210134189"]},{"raw_affiliation_string":"Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020386089","display_name":"Zhenjie Yang","orcid":"https://orcid.org/0000-0002-2414-5058"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenjie Yang","raw_affiliation_strings":["Xiamen University, Xiamen, China"],"raw_orcid":"https://orcid.org/0000-0002-2414-5058","affiliations":[{"raw_affiliation_string":"Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108819118","display_name":"Hongwei Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hongwei Wu","raw_affiliation_strings":["Xiamen Network Information Security Joint Laboratory, Xiamen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xiamen Network Information Security Joint Laboratory, Xiamen, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":3.4262,"has_fulltext":true,"cited_by_count":62,"citation_normalized_percentile":{"value":0.93976502,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":"8","issue":null,"first_page":"174922","last_page":"174930"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","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/T11448","display_name":"Face recognition and analysis","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/T10828","display_name":"Biometric Identification and Security","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9973999857902527,"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":0.8231489658355713},{"id":"https://openalex.org/keywords/receptive-field","display_name":"Receptive field","score":0.7157254219055176},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6691925525665283},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6503356099128723},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6481412649154663},{"id":"https://openalex.org/keywords/cascade","display_name":"Cascade","score":0.5974897742271423},{"id":"https://openalex.org/keywords/pascal","display_name":"Pascal (unit)","score":0.5620248317718506},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5606264472007751},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.5229576230049133},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.4876755475997925},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4676964282989502},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.42865797877311707},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4220072329044342},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.3932696580886841},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08861643075942993}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8231489658355713},{"id":"https://openalex.org/C19071747","wikidata":"https://www.wikidata.org/wiki/Q1755207","display_name":"Receptive field","level":2,"score":0.7157254219055176},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6691925525665283},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6503356099128723},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6481412649154663},{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.5974897742271423},{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.5620248317718506},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5606264472007751},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.5229576230049133},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.4876755475997925},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4676964282989502},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.42865797877311707},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4220072329044342},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.3932696580886841},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08861643075942993},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3023782","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3023782","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09195457.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d3ddd40860564825b2408bb26a12aa55","is_oa":true,"landing_page_url":"https://doaj.org/article/d3ddd40860564825b2408bb26a12aa55","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 174922-174930 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3023782","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3023782","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09195457.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6299999952316284,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G3151893638","display_name":null,"funder_award_id":"XMUMRF/2019-C4/IECE/0008","funder_id":"https://openalex.org/F4320325434","funder_display_name":"Xiamen University"}],"funders":[{"id":"https://openalex.org/F4320325434","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3085394167.pdf","grobid_xml":"https://content.openalex.org/works/W3085394167.grobid-xml"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W182571476","https://openalex.org/W1686810756","https://openalex.org/W1799366690","https://openalex.org/W1834627138","https://openalex.org/W1849007038","https://openalex.org/W1934410531","https://openalex.org/W1970456555","https://openalex.org/W2012885984","https://openalex.org/W2034025266","https://openalex.org/W2041497292","https://openalex.org/W2097117768","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2209882149","https://openalex.org/W2341528187","https://openalex.org/W2477332545","https://openalex.org/W2477460793","https://openalex.org/W2495387757","https://openalex.org/W2523915246","https://openalex.org/W2578555672","https://openalex.org/W2592939477","https://openalex.org/W2604749796","https://openalex.org/W2751314021","https://openalex.org/W2752632790","https://openalex.org/W2758030817","https://openalex.org/W2769114105","https://openalex.org/W2784163702","https://openalex.org/W2963377935","https://openalex.org/W2963566548","https://openalex.org/W2963604034","https://openalex.org/W2963721882","https://openalex.org/W2967283245","https://openalex.org/W2969985801","https://openalex.org/W3006322985","https://openalex.org/W3101998545","https://openalex.org/W3103152812","https://openalex.org/W6607458078","https://openalex.org/W6637373629","https://openalex.org/W6638444622","https://openalex.org/W6660695881","https://openalex.org/W6721514182","https://openalex.org/W6746123559"],"related_works":["https://openalex.org/W2336272890","https://openalex.org/W4308999381","https://openalex.org/W3183843611","https://openalex.org/W4312238398","https://openalex.org/W3211418293","https://openalex.org/W4308999963","https://openalex.org/W4312081214","https://openalex.org/W2059356388","https://openalex.org/W325114128","https://openalex.org/W2970510692"],"abstract_inverted_index":{"With":[0],"the":[1,12,22,27,54,85,94,107,117,121,126,134,138],"continuous":[2],"development":[3],"of":[4,53,84,109,137],"deep":[5],"learning,":[6],"face":[7,32],"detection":[8],"methods":[9],"have":[10],"made":[11],"greatest":[13],"progress.":[14],"For":[15],"real-time":[16],"detection,":[17],"cascade":[18],"CNN":[19],"based":[20],"on":[21,116,120,125,133],"lightweight":[23],"model":[24,68],"is":[25,46,112],"still":[26,58],"dominant":[28],"structure":[29,149],"that":[30,106],"predicts":[31],"in":[33,62,142],"a":[34,50,73],"coarse-to-fine":[35],"manner":[36],"with":[37,144],"strong":[38],"generalization":[39,69],"ability.":[40],"Compared":[41],"to":[42,92],"other":[43],"methods,":[44],"it":[45],"not":[47],"required":[48],"for":[49,99],"fixed":[51],"size":[52],"input.":[55],"However,":[56],"MTCNN":[57,145],"has":[59],"poor":[60],"performance":[61,108],"detecting":[63],"tiny":[64],"targets.":[65,101],"To":[66],"improve":[67],"ability,":[70],"we":[71],"propose":[72],"Receptive":[74],"Field":[75],"Enhanced":[76],"Multi-Task":[77],"Cascaded":[78],"CNN.":[79],"This":[80],"network":[81,111],"takes":[82],"advantage":[83],"Inception-V2":[86],"block":[87,91],"and":[88,97,128,131],"receptive":[89],"field":[90],"enhance":[93],"feature":[95],"discriminability":[96],"robustness":[98],"small":[100],"The":[102],"experimental":[103],"results":[104],"show":[105],"our":[110,148],"improved":[113],"by":[114],"1.08%":[115],"AFW,":[118],"2.84%":[119],"PASCAL":[122],"FACE,":[123],"1.31%":[124],"FDDB,":[127],"2.3%,":[129],"2.1%,":[130],"6.6%":[132],"three":[135],"sub-datasets":[136],"WIDER":[139],"FACE":[140],"benchmark":[141],"comparison":[143],"respectively.":[146],"Furthermore,":[147],"uses":[150],"16%":[151],"fewer":[152],"parameters.":[153]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":10}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
