{"id":"https://openalex.org/W2563310060","doi":"https://doi.org/10.1109/icip.2016.7532771","title":"Localize heavily occluded human faces via deep segmentation","display_name":"Localize heavily occluded human faces via deep segmentation","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2563310060","doi":"https://doi.org/10.1109/icip.2016.7532771","mag":"2563310060"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2016.7532771","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7532771","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 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/A5103144603","display_name":"Kaihao Zhang","orcid":"https://orcid.org/0000-0002-4317-660X"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"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"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kaihao Zhang","raw_affiliation_strings":["Chinese Academy of Sciences, Institute of Automation, China","Statistical Machine Intelligence & LEarning, University of Electronic Science and Technology of China, China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Institute of Automation, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]},{"raw_affiliation_string":"Statistical Machine Intelligence & LEarning, University of Electronic Science and Technology of China, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024579621","display_name":"Yongzhen Huang","orcid":"https://orcid.org/0000-0003-4389-9805"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongzhen Huang","raw_affiliation_strings":["Chinese Academy of Sciences, Institute of Automation, China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Institute of Automation, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112749024","display_name":"Ran He","orcid":"https://orcid.org/0000-0002-3807-991X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ran He","raw_affiliation_strings":["Chinese Academy of Sciences, Institute of Automation, China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Institute of Automation, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079051307","display_name":"Hong Wu","orcid":"https://orcid.org/0000-0002-7019-8046"},"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":"Hong Wu","raw_affiliation_strings":["Statistical Machine Intelligence & LEarning, University of Electronic Science and Technology of China, China"],"affiliations":[{"raw_affiliation_string":"Statistical Machine Intelligence & LEarning, University of Electronic Science and Technology of China, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5115602506","display_name":"Liang Wang","orcid":"https://orcid.org/0000-0001-5224-8647"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Wang","raw_affiliation_strings":["Chinese Academy of Sciences, Institute of Automation, China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Institute of Automation, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5103144603"],"corresponding_institution_ids":["https://openalex.org/I150229711","https://openalex.org/I19820366","https://openalex.org/I4210112150"],"apc_list":null,"apc_paid":null,"fwci":0.334,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.67992481,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2311","last_page":"2315"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","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/T11448","display_name":"Face recognition and analysis","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/T10057","display_name":"Face and Expression Recognition","score":0.9994000196456909,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9991999864578247,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8400487899780273},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8068722486495972},{"id":"https://openalex.org/keywords/softmax-function","display_name":"Softmax function","score":0.7747293710708618},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6859410405158997},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6750156879425049},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6252774000167847},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5925843715667725},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5473001003265381},{"id":"https://openalex.org/keywords/sliding-window-protocol","display_name":"Sliding window protocol","score":0.4775453507900238},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4730631113052368},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4712795615196228},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.45287665724754333},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4512670040130615},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.435712993144989},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.3396233320236206},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.22048699855804443}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8400487899780273},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8068722486495972},{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.7747293710708618},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6859410405158997},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6750156879425049},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6252774000167847},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5925843715667725},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5473001003265381},{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.4775453507900238},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4730631113052368},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4712795615196228},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.45287665724754333},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4512670040130615},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.435712993144989},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.3396233320236206},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.22048699855804443},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2016.7532771","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7532771","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321610","display_name":"Universit\u00e0 degli Studi di Milano-Bicocca","ror":"https://ror.org/01ynf4891"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1849007038","https://openalex.org/W1934410531","https://openalex.org/W1994215930","https://openalex.org/W2015268479","https://openalex.org/W2044584741","https://openalex.org/W2047508432","https://openalex.org/W2070870580","https://openalex.org/W2097117768","https://openalex.org/W2111372597","https://openalex.org/W2113120414","https://openalex.org/W2133327040","https://openalex.org/W2150688176","https://openalex.org/W2163605009","https://openalex.org/W2164598857","https://openalex.org/W2169696215","https://openalex.org/W2247274765","https://openalex.org/W2402287763","https://openalex.org/W6638943231","https://openalex.org/W6649023448","https://openalex.org/W6662335928","https://openalex.org/W6679831340","https://openalex.org/W6682250864","https://openalex.org/W6684191040","https://openalex.org/W6691127938","https://openalex.org/W6713211323"],"related_works":["https://openalex.org/W3107204728","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"],"abstract_inverted_index":{"Localizing":[0],"heavily":[1,35,82,136],"occluded":[2,36,83,137],"human":[3,23,84,95,138],"faces":[4,116],"is":[5,77,129],"a":[6,30,62,89,111,130],"challenging":[7],"problem":[8],"in":[9,73],"facial":[10],"detection.":[11],"Previous":[12],"methods":[13],"mainly":[14],"employ":[15],"sliding":[16,106],"windows":[17,21],"by":[18],"determining":[19],"whether":[20],"include":[22],"faces.":[24,85],"In":[25],"this":[26],"paper,":[27],"we":[28,65,87,109],"provide":[29],"novel":[31],"segmentation-based":[32],"perspective":[33],"for":[34],"face":[37],"localization":[38],"with":[39],"deep":[40],"convolutional":[41,57],"neural":[42],"networks":[43],"(CNN).":[44],"Our":[45,97],"model":[46,113],"takes":[47],"an":[48,74],"image":[49],"as":[50],"input":[51],"without":[52],"complicated":[53],"pre-processing.":[54],"After":[55],"several":[56],"layers,":[58],"fully-connected":[59],"layers":[60],"and":[61],"softmax":[63],"classifier,":[64],"can":[66],"predict":[67],"the":[68,78,94,104],"labels":[69],"of":[70],"all":[71],"pixels":[72],"image,":[75],"which":[76],"key":[79],"to":[80,92,114,117,134],"localize":[81,93,115,135],"Finally,":[86],"search":[88],"minimal":[90],"rectangle":[91],"face.":[96,139],"detector":[98],"needs":[99],"neither":[100],"complex":[101],"pre-processing":[102],"nor":[103],"time-consuming":[105],"window.":[107],"Besides,":[108],"use":[110],"single":[112],"further":[118],"alleviate":[119],"computational":[120],"complexity.":[121],"Experimental":[122],"results":[123],"show":[124],"that":[125],"our":[126],"proposed":[127],"method":[128],"very":[131],"effective":[132],"way":[133]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2017,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
