{"id":"https://openalex.org/W2902503646","doi":"https://doi.org/10.1109/icpr.2018.8545033","title":"Automatic Facial Attractiveness Prediction by Deep Multi-Task Learning","display_name":"Automatic Facial Attractiveness Prediction by Deep Multi-Task Learning","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2902503646","doi":"https://doi.org/10.1109/icpr.2018.8545033","mag":"2902503646"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2018.8545033","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545033","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","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/A5102616024","display_name":"Lian Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lian Gao","raw_affiliation_strings":["IRIP Lab, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"IRIP Lab, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100662467","display_name":"Weixin Li","orcid":"https://orcid.org/0000-0002-5093-5635"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weixin Li","raw_affiliation_strings":["Advanced Innovation Center for Big Data and Brain Computing, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Advanced Innovation Center for Big Data and Brain Computing, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101283230","display_name":"Zehua Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zehua Huang","raw_affiliation_strings":["TuSimple, San Diego, USA"],"affiliations":[{"raw_affiliation_string":"TuSimple, San Diego, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056972984","display_name":"Di Huang","orcid":"https://orcid.org/0000-0002-2412-9330"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Di Huang","raw_affiliation_strings":["IRIP Lab, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"IRIP Lab, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5115589096","display_name":"Yunhong Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunhong Wang","raw_affiliation_strings":["IRIP Lab, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"IRIP Lab, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5102616024"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":1.149,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.84061438,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3592","last_page":"3597"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9994999766349792,"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":0.9994999766349792,"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/T11118","display_name":"Evolutionary Psychology and Human Behavior","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11094","display_name":"Face Recognition and Perception","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/facial-attractiveness","display_name":"Facial attractiveness","score":0.8488516211509705},{"id":"https://openalex.org/keywords/landmark","display_name":"Landmark","score":0.7579355835914612},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7556142807006836},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7505764961242676},{"id":"https://openalex.org/keywords/beautification","display_name":"Beautification","score":0.7180390357971191},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5745994448661804},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5542504191398621},{"id":"https://openalex.org/keywords/attractiveness","display_name":"Attractiveness","score":0.5126928091049194},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43378424644470215},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3878624141216278},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.36529016494750977},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.059648752212524414}],"concepts":[{"id":"https://openalex.org/C2994111384","wikidata":"https://www.wikidata.org/wiki/Q758234","display_name":"Facial attractiveness","level":3,"score":0.8488516211509705},{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.7579355835914612},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7556142807006836},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7505764961242676},{"id":"https://openalex.org/C2777972131","wikidata":"https://www.wikidata.org/wiki/Q4877642","display_name":"Beautification","level":2,"score":0.7180390357971191},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5745994448661804},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5542504191398621},{"id":"https://openalex.org/C31173074","wikidata":"https://www.wikidata.org/wiki/Q2632514","display_name":"Attractiveness","level":2,"score":0.5126928091049194},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43378424644470215},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3878624141216278},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36529016494750977},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.059648752212524414},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C11171543","wikidata":"https://www.wikidata.org/wiki/Q41630","display_name":"Psychoanalysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2018.8545033","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545033","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","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":46,"referenced_works":["https://openalex.org/W204612701","https://openalex.org/W1522301498","https://openalex.org/W1834627138","https://openalex.org/W1836465849","https://openalex.org/W1964993232","https://openalex.org/W1972968514","https://openalex.org/W1974387747","https://openalex.org/W1987208496","https://openalex.org/W1988047116","https://openalex.org/W1993741516","https://openalex.org/W1998808035","https://openalex.org/W2003118627","https://openalex.org/W2008072751","https://openalex.org/W2028109154","https://openalex.org/W2047508432","https://openalex.org/W2096733369","https://openalex.org/W2102836959","https://openalex.org/W2115252128","https://openalex.org/W2143761310","https://openalex.org/W2152186880","https://openalex.org/W2163605009","https://openalex.org/W2169866542","https://openalex.org/W2186615578","https://openalex.org/W2229978099","https://openalex.org/W2231999017","https://openalex.org/W2548780814","https://openalex.org/W2606080779","https://openalex.org/W2620075774","https://openalex.org/W2751803194","https://openalex.org/W2913340405","https://openalex.org/W2963377935","https://openalex.org/W2964118336","https://openalex.org/W2964121744","https://openalex.org/W3099206234","https://openalex.org/W6608207920","https://openalex.org/W6631190155","https://openalex.org/W6638667902","https://openalex.org/W6638891565","https://openalex.org/W6677618333","https://openalex.org/W6682525936","https://openalex.org/W6684191040","https://openalex.org/W6686509673","https://openalex.org/W6689124258","https://openalex.org/W6689559109","https://openalex.org/W6696405545","https://openalex.org/W6765986828"],"related_works":["https://openalex.org/W2575018051","https://openalex.org/W2948519955","https://openalex.org/W4380611720","https://openalex.org/W4242102259","https://openalex.org/W1994528771","https://openalex.org/W2907895567","https://openalex.org/W2947344805","https://openalex.org/W2901659106","https://openalex.org/W3198701297","https://openalex.org/W4311607363"],"abstract_inverted_index":{"Facial":[0],"Attractiveness":[1],"Prediction":[2],"(FAP)":[3],"is":[4,78,95,106],"a":[5,21,43,75,102],"useful":[6],"yet":[7],"challenging":[8],"problem":[9],"in":[10,62,119],"the":[11,28,32,37,69,83,98,110,138,141],"domain":[12],"of":[13,48,59,65,112,121,140],"computer":[14],"vision.":[15],"In":[16],"this":[17],"paper,":[18],"we":[19],"propose":[20],"deep":[22,30],"learning":[23,45],"based":[24],"approach.":[25],"Different":[26],"from":[27],"existing":[29],"methods,":[31],"proposed":[33,93,142],"one":[34],"models":[35],"both":[36,58],"texture":[38],"and":[39,52,88,101,127],"shape":[40],"clues":[41],"within":[42],"multi-task":[44],"framework":[46],"consisting":[47],"attractiveness":[49,64,90],"score":[50],"prediction":[51,103],"fiducial":[53],"landmark":[54,86],"localization,":[55],"thus":[56],"highlighting":[57],"their":[60],"roles":[61],"assessing":[63],"faces.":[66],"Considering":[67],"that":[68],"training":[70],"data":[71],"are":[72,132],"not":[73],"extensive,":[74],"lightweight":[76],"CNN":[77],"designed":[79],"to":[80],"jointly":[81],"learn":[82],"facial":[84,89,124],"representation,":[85],"location,":[87],"score.":[91],"The":[92,134],"method":[94],"evaluated":[96],"on":[97],"SCUT-FBP":[99],"database,":[100],"correlation":[104],"0.92,":[105],"delivered,":[107],"which":[108],"shows":[109],"effectiveness":[111],"our":[113],"method.":[114,143],"Furthermore,":[115],"two":[116],"additional":[117],"experiments":[118],"terms":[120],"comparison":[122],"between":[123],"images":[125],"before":[126],"after":[128],"make-up":[129],"or":[130],"beautification":[131],"conducted.":[133],"results":[135],"also":[136],"prove":[137],"advantage":[139]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}