{"id":"https://openalex.org/W4210250172","doi":"https://doi.org/10.1109/fg52635.2021.9667036","title":"Efficient Facial Landmark Detector by Knowledge Distillation","display_name":"Efficient Facial Landmark Detector by Knowledge Distillation","publication_year":2021,"publication_date":"2021-12-15","ids":{"openalex":"https://openalex.org/W4210250172","doi":"https://doi.org/10.1109/fg52635.2021.9667036"},"language":"en","primary_location":{"id":"doi:10.1109/fg52635.2021.9667036","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fg52635.2021.9667036","pdf_url":null,"source":{"id":"https://openalex.org/S4363608446","display_name":"2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)","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/A5003483009","display_name":"Yuyang Sha","orcid":null},"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/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuyang Sha","raw_affiliation_strings":["Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, Beijing, CAS, China"],"affiliations":[{"raw_affiliation_string":"Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, Beijing, CAS, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5003483009"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"],"apc_list":null,"apc_paid":null,"fwci":0.196,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.59821429,"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":"1","last_page":"8"},"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":0.9921000003814697,"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/T10057","display_name":"Face and Expression Recognition","score":0.9743000268936157,"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/landmark","display_name":"Landmark","score":0.9676013588905334},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7878522872924805},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6393324136734009},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.6042260527610779},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.5954447388648987},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.586713433265686},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.47820377349853516},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.42132627964019775},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38465815782546997},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3559010326862335}],"concepts":[{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.9676013588905334},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7878522872924805},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6393324136734009},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.6042260527610779},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.5954447388648987},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.586713433265686},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.47820377349853516},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42132627964019775},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38465815782546997},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3559010326862335},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fg52635.2021.9667036","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fg52635.2021.9667036","pdf_url":null,"source":{"id":"https://openalex.org/S4363608446","display_name":"2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.8100000023841858,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W1821462560","https://openalex.org/W1896424170","https://openalex.org/W1960706641","https://openalex.org/W1990937109","https://openalex.org/W2012885984","https://openalex.org/W2015229219","https://openalex.org/W2058961190","https://openalex.org/W2111372597","https://openalex.org/W2157285372","https://openalex.org/W2194775991","https://openalex.org/W2283863529","https://openalex.org/W2307770531","https://openalex.org/W2519753233","https://openalex.org/W2554268477","https://openalex.org/W2736671157","https://openalex.org/W2740020909","https://openalex.org/W2770121394","https://openalex.org/W2798730128","https://openalex.org/W2798898313","https://openalex.org/W2897558462","https://openalex.org/W2903396356","https://openalex.org/W2944892540","https://openalex.org/W2948303854","https://openalex.org/W2952787292","https://openalex.org/W2961224374","https://openalex.org/W2962793481","https://openalex.org/W2962819150","https://openalex.org/W2962925415","https://openalex.org/W2963073614","https://openalex.org/W2963125010","https://openalex.org/W2963163009","https://openalex.org/W2963249562","https://openalex.org/W2963544187","https://openalex.org/W2963789946","https://openalex.org/W2963993755","https://openalex.org/W2964062189","https://openalex.org/W2964297864","https://openalex.org/W2982772166","https://openalex.org/W2990952853","https://openalex.org/W3014641072","https://openalex.org/W3035197297","https://openalex.org/W3176383825","https://openalex.org/W4288558691","https://openalex.org/W6638523607","https://openalex.org/W6639495226","https://openalex.org/W6641044740","https://openalex.org/W6685786476","https://openalex.org/W6697925102","https://openalex.org/W6726870146","https://openalex.org/W6729966448","https://openalex.org/W6740474667","https://openalex.org/W6755288431","https://openalex.org/W6756633790","https://openalex.org/W6759845760","https://openalex.org/W6767071366","https://openalex.org/W6797728528"],"related_works":["https://openalex.org/W2056853153","https://openalex.org/W2057559274","https://openalex.org/W2005087563","https://openalex.org/W2378111931","https://openalex.org/W2052388267","https://openalex.org/W2950647290","https://openalex.org/W1968481813","https://openalex.org/W2620829895","https://openalex.org/W2356918560","https://openalex.org/W4243161226"],"abstract_inverted_index":{"Facial":[0],"landmark":[1,29,76,105],"detection":[2],"aims":[3],"to":[4,56,117,133,138],"locate":[5],"some":[6],"predefined":[7],"points":[8],"on":[9,32],"human":[10],"face":[11],"images,":[12],"which":[13,79,107],"is":[14],"the":[15,44,57,82,113,118,129,135,140,145,151],"basis":[16],"of":[17,154],"many":[18,60],"facial":[19,28,75,104],"analysis":[20],"tasks":[21],"and":[22,41,47,85],"applications.":[23,64],"Compared":[24],"with":[25,93],"traditional":[26],"methods,":[27],"detector":[30,77],"based":[31],"deep":[33],"learning":[34,127],"has":[35],"made":[36],"significant":[37],"progress":[38],"in":[39,62],"accuracy":[40],"efficiency.":[42],"However,":[43],"model":[45,83,116,137],"parameters":[46],"computational":[48,86],"cost":[49,87],"have":[50],"not":[51],"received":[52],"enough":[53],"attention,":[54],"leading":[55],"algorithm":[58],"facing":[59],"challenges":[61],"practical":[63],"In":[65,122],"this":[66],"paper,":[67],"we":[68,124],"propose":[69],"a":[70,98],"novel":[71],"method":[72],"named":[73],"efficient":[74],"(EFLD),":[78],"significantly":[80],"compresses":[81],"size":[84],"while":[88],"achieving":[89],"superior":[90,152],"performance":[91,153],"compared":[92],"state-of-the-art":[94,158],"frameworks.":[95],"We":[96],"introduce":[97],"knowledge":[99,130],"distillation":[100,131],"framework":[101,132],"suitable":[102],"for":[103],"detection,":[106],"can":[108],"transfer":[109],"geometric":[110],"information":[111],"from":[112],"pre-trained":[114],"teacher":[115,146],"lightweight":[119],"student":[120,136],"model.":[121,147],"addition,":[123],"integrate":[125],"adversarial":[126],"into":[128],"guide":[134],"imitate":[139],"heatmap":[141],"distribution":[142],"generated":[143],"by":[144],"Extensive":[148],"experiments":[149],"demonstrate":[150],"our":[155],"approach":[156],"against":[157],"methods.":[159]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}