{"id":"https://openalex.org/W2790299973","doi":"https://doi.org/10.1109/icip.2017.8296992","title":"Occlusion robust face recognition based on mask learning","display_name":"Occlusion robust face recognition based on mask learning","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2790299973","doi":"https://doi.org/10.1109/icip.2017.8296992","mag":"2790299973"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2017.8296992","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296992","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","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/A5100784791","display_name":"Weitao Wan","orcid":"https://orcid.org/0000-0002-6601-4873"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weitao Wan","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, P.R. China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, P.R. China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100668653","display_name":"Jiansheng Chen","orcid":"https://orcid.org/0000-0002-2040-7938"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiansheng Chen","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, P.R. China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, P.R. China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100784791"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.9102,"has_fulltext":false,"cited_by_count":71,"citation_normalized_percentile":{"value":0.84385704,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3795","last_page":"3799"},"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/T10057","display_name":"Face and Expression Recognition","score":0.9961000084877014,"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":0.9957000017166138,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.822171151638031},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8044430017471313},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7749104499816895},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7540543079376221},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7106055021286011},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.6154079437255859},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6107568740844727},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5645155906677246},{"id":"https://openalex.org/keywords/three-dimensional-face-recognition","display_name":"Three-dimensional face recognition","score":0.5012483596801758},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4945795238018036},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44741928577423096},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4363098442554474},{"id":"https://openalex.org/keywords/occlusion","display_name":"Occlusion","score":0.4324919283390045},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.31138741970062256}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.822171151638031},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8044430017471313},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7749104499816895},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7540543079376221},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7106055021286011},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.6154079437255859},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6107568740844727},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5645155906677246},{"id":"https://openalex.org/C88799230","wikidata":"https://www.wikidata.org/wiki/Q3398329","display_name":"Three-dimensional face recognition","level":5,"score":0.5012483596801758},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4945795238018036},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44741928577423096},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4363098442554474},{"id":"https://openalex.org/C2776268601","wikidata":"https://www.wikidata.org/wiki/Q968808","display_name":"Occlusion","level":2,"score":0.4324919283390045},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.31138741970062256},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","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/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2017.8296992","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296992","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7599999904632568,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1781265","https://openalex.org/W603908379","https://openalex.org/W1509966554","https://openalex.org/W1514535095","https://openalex.org/W1721634477","https://openalex.org/W1950843348","https://openalex.org/W2019464758","https://openalex.org/W2073575766","https://openalex.org/W2096733369","https://openalex.org/W2098017479","https://openalex.org/W2107369107","https://openalex.org/W2134083628","https://openalex.org/W2145526234","https://openalex.org/W2155893237","https://openalex.org/W2166167289","https://openalex.org/W2194775991","https://openalex.org/W2294059674","https://openalex.org/W2341528187","https://openalex.org/W2520774990","https://openalex.org/W2565575913","https://openalex.org/W2994340921","https://openalex.org/W3099206234","https://openalex.org/W3101998545","https://openalex.org/W3122534566","https://openalex.org/W6618372016","https://openalex.org/W6635552349","https://openalex.org/W6687483927","https://openalex.org/W6696761078","https://openalex.org/W6789421156"],"related_works":["https://openalex.org/W2166031825","https://openalex.org/W2918845005","https://openalex.org/W4387163326","https://openalex.org/W2040482211","https://openalex.org/W2185537520","https://openalex.org/W3108145925","https://openalex.org/W325114128","https://openalex.org/W2336272890","https://openalex.org/W4312238398","https://openalex.org/W4308999963"],"abstract_inverted_index":{"Face":[0],"occlusion":[1],"has":[2],"been":[3],"a":[4,67,90],"long":[5],"standing":[6],"challenging":[7],"issue":[8],"in":[9,38,74,157],"face":[10,20,50,57,103,158],"recognition.":[11,159],"In":[12],"the":[13,30,35,44,48,65,84,112,117,130,150],"state-of-the-art":[14],"deep":[15],"Convolutional":[16],"Neural":[17],"Network":[18],"(CNN)":[19],"recognition":[21],"models,":[22],"occluded":[23,56,102,131,142],"facial":[24,119,132],"parts":[25,37,120],"are":[26,127],"generally":[27],"embedded":[28],"into":[29],"learned":[31],"features":[32],"together":[33],"with":[34],"non-occluded":[36,118],"an":[39],"equivalent":[40],"manner.":[41],"As":[42],"such,":[43],"discriminative":[45],"power":[46],"of":[47,93,138,152],"generated":[49],"representation":[51],"may":[52],"be":[53,72],"weakened":[54],"for":[55,100],"images.":[58,104],"To":[59],"address":[60],"this":[61],"problem,":[62],"we":[63],"propose":[64],"MaskNet,":[66],"trainable":[68],"module":[69],"which":[70],"can":[71,147],"included":[73],"existing":[75],"CNN":[76,153],"architectures.":[77],"With":[78],"end-to-end":[79],"training":[80],"supervised":[81],"by":[82,116,129],"only":[83],"personal":[85],"identity":[86],"labels,":[87],"MaskNet":[88,106,146],"learns":[89],"proper":[91],"way":[92],"adaptively":[94],"generating":[95],"different":[96,101],"feature":[97],"map":[98],"masks":[99],"Intuitively,":[105],"automatically":[107],"assigns":[108],"higher":[109],"weights":[110,123],"to":[111,124],"hidden":[113],"units":[114],"activated":[115,128],"and":[121,140],"lower":[122],"those":[125],"that":[126,145],"parts.":[133],"Experiments":[134],"on":[135],"datasets":[136],"consisting":[137],"real-life":[139],"synthetic":[141],"faces":[143],"demonstrate":[144],"effectively":[148],"improve":[149],"robustness":[151],"models":[154],"towards":[155],"occlusions":[156]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":20},{"year":2021,"cited_by_count":18},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":8}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}