{"id":"https://openalex.org/W3005538018","doi":"https://doi.org/10.1145/3374760","title":"Joint Stacked Hourglass Network and Salient Region Attention Refinement for Robust Face Alignment","display_name":"Joint Stacked Hourglass Network and Salient Region Attention Refinement for Robust Face Alignment","publication_year":2020,"publication_date":"2020-02-17","ids":{"openalex":"https://openalex.org/W3005538018","doi":"https://doi.org/10.1145/3374760","mag":"3005538018"},"language":"en","primary_location":{"id":"doi:10.1145/3374760","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3374760","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Multimedia Computing, Communications, and Applications","raw_type":"journal-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/A5100427771","display_name":"Junfeng Zhang","orcid":"https://orcid.org/0000-0001-7660-0684"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junfeng Zhang","raw_affiliation_strings":["Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056953478","display_name":"Haifeng Hu","orcid":"https://orcid.org/0000-0002-4884-323X"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haifeng Hu","raw_affiliation_strings":["Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China"],"raw_orcid":"https://orcid.org/0000-0002-4884-323X","affiliations":[{"raw_affiliation_string":"Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081220735","display_name":"Guobin Shen","orcid":"https://orcid.org/0000-0002-4069-2107"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guobin Shen","raw_affiliation_strings":["Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":0.8625,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.75111339,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"16","issue":"1","first_page":"1","last_page":"18"},"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":0.9772999882698059,"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":0.9758999943733215,"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":0.8538755178451538},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7152500152587891},{"id":"https://openalex.org/keywords/landmark","display_name":"Landmark","score":0.7111032605171204},{"id":"https://openalex.org/keywords/hourglass","display_name":"Hourglass","score":0.708367645740509},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6409416198730469},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5974505543708801},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5918943881988525},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.5860928297042847},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.580123245716095},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4595377445220947},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4578896462917328},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4057255685329437},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09092029929161072}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8538755178451538},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7152500152587891},{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.7111032605171204},{"id":"https://openalex.org/C127532173","wikidata":"https://www.wikidata.org/wiki/Q179904","display_name":"Hourglass","level":2,"score":0.708367645740509},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6409416198730469},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5974505543708801},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5918943881988525},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.5860928297042847},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.580123245716095},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4595377445220947},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4578896462917328},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4057255685329437},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09092029929161072},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"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/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3374760","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3374760","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Multimedia Computing, Communications, and Applications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.6800000071525574}],"awards":[{"id":"https://openalex.org/G1786224844","display_name":null,"funder_award_id":"61673402, 61273270, and 60802069","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2194486905","display_name":null,"funder_award_id":"19lgjc03","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G4228998522","display_name":null,"funder_award_id":"2017A030311029","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1682276745","https://openalex.org/W1686810756","https://openalex.org/W1915668717","https://openalex.org/W1976948919","https://openalex.org/W1990937109","https://openalex.org/W2012885984","https://openalex.org/W2036868818","https://openalex.org/W2038952578","https://openalex.org/W2058961190","https://openalex.org/W2087681821","https://openalex.org/W2112796928","https://openalex.org/W2136000821","https://openalex.org/W2136391815","https://openalex.org/W2152826865","https://openalex.org/W2157285372","https://openalex.org/W2166694921","https://openalex.org/W2186222003","https://openalex.org/W2194775991","https://openalex.org/W2283863529","https://openalex.org/W2307770531","https://openalex.org/W2341528187","https://openalex.org/W2345945060","https://openalex.org/W2462523589","https://openalex.org/W2474575620","https://openalex.org/W2508691887","https://openalex.org/W2518965973","https://openalex.org/W2519753233","https://openalex.org/W2554268477","https://openalex.org/W2557290168","https://openalex.org/W2736728583","https://openalex.org/W2740020909","https://openalex.org/W2887748972","https://openalex.org/W2951392520","https://openalex.org/W2952074561","https://openalex.org/W2963253045","https://openalex.org/W2963789946","https://openalex.org/W2964105113","https://openalex.org/W2964239703","https://openalex.org/W3101998545","https://openalex.org/W3102288316","https://openalex.org/W3105198140","https://openalex.org/W4242177601","https://openalex.org/W4301409532"],"related_works":["https://openalex.org/W2008001194","https://openalex.org/W2056853153","https://openalex.org/W2057559274","https://openalex.org/W2512390310","https://openalex.org/W2059645356","https://openalex.org/W2026924879","https://openalex.org/W2967400411","https://openalex.org/W1993438337","https://openalex.org/W1977899511","https://openalex.org/W4288277645"],"abstract_inverted_index":{"Facial":[0,196],"landmark":[1],"detection":[2],"aims":[3],"to":[4,60,132,153,171],"locate":[5],"keypoints":[6],"for":[7,44,84,168],"facial":[8,20,68,89],"images,":[9],"which":[10,107],"typically":[11],"suffer":[12],"from":[13,140],"variations":[14],"caused":[15],"by":[16],"arbitrary":[17],"pose,":[18],"diverse":[19],"expressions,":[21],"and":[22,39,70,87,114,129,163,194],"partial":[23],"occlusion.":[24],"In":[25],"this":[26,50],"article,":[27],"we":[28,52,78,145],"propose":[29],"a":[30,35,55,66,72,80,103,120,147,155],"coarse-to-fine":[31],"framework":[32],"that":[33,203],"joins":[34],"stacked":[36,81,94],"hourglass":[37,82,95],"network":[38,83,96],"salient":[40,148],"region":[41,57,69,149],"attention":[42,150],"refinement":[43,151,170],"robust":[45],"face":[46],"alignment.":[47],"To":[48],"achieve":[49,172,207],"goal,":[51],"first":[53],"present":[54,146],"multi-scale":[56],"learning":[58],"module":[59,152],"analyze":[61],"the":[62,93,111,134,160,165,186,192,200,212],"structure":[63],"information":[64],"at":[65],"different":[67],"extract":[71,154],"strong":[73],"discriminative":[74],"deep":[75],"feature.":[76],"Then":[77],"employ":[79],"heatmap":[85,135,142,161],"regression":[86,136,143],"initial":[88],"landmarks":[90,169],"prediction.":[91,174],"Specifically,":[92],"introduces":[97],"an":[98],"improved":[99],"Inception-ResNet":[100],"unit":[101],"as":[102],"basic":[104],"building":[105],"block,":[106],"can":[108,206],"effectively":[109],"improve":[110],"receptive":[112],"field":[113],"learn":[115],"contextual":[116],"feature":[117,157,167],"representations.":[118],"Meanwhile,":[119],"novel":[121],"loss":[122],"function":[123],"takes":[124],"into":[125],"account":[126],"global":[127],"weights":[128,131],"local":[130],"make":[133],"more":[137,208],"accurate.":[138],"Different":[139],"existing":[141],"models,":[144],"precise":[156],"based":[158],"on":[159],"regression,":[162],"utilize":[164],"filtered":[166],"accurate":[173],"Extensive":[175],"experimental":[176],"results":[177],"of":[178],"several":[179],"challenging":[180],"datasets":[181],"(including":[182],"300":[183],"Faces":[184,190,198],"in":[185,191,199],"Wild,":[187,193],"Caltech":[188],"Occluded":[189],"Annotated":[195],"Landmarks":[197],"Wild)":[201],"confirm":[202],"our":[204],"approach":[205],"competitive":[209],"performance":[210],"than":[211],"most":[213],"advanced":[214],"algorithms.":[215]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}