{"id":"https://openalex.org/W4414404728","doi":"https://doi.org/10.1109/access.2025.3612890","title":"Facial Landmark Detection and Head Pose Estimation of Occluded Faces Based on Stable Diffusion Image Completion","display_name":"Facial Landmark Detection and Head Pose Estimation of Occluded Faces Based on Stable Diffusion Image Completion","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4414404728","doi":"https://doi.org/10.1109/access.2025.3612890"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3612890","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3612890","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3612890","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057017654","display_name":"Wenzhangzhi Guo","orcid":"https://orcid.org/0000-0003-2549-4679"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]},{"id":"https://openalex.org/I4210151646","display_name":"SGS (Canada)","ror":"https://ror.org/05w5dvb13","country_code":"CA","type":"company","lineage":["https://openalex.org/I4210151646","https://openalex.org/I4210158066"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Wenzhangzhi Guo","raw_affiliation_strings":["Medical Computer Vision and Robotics Laboratory, University of Toronto Mississauga, Mississauga, ON, Canada","Medical Computer Vision and Robotics Lab, University of Toronto, Toronto, ON, Canada"],"affiliations":[{"raw_affiliation_string":"Medical Computer Vision and Robotics Laboratory, University of Toronto Mississauga, Mississauga, ON, Canada","institution_ids":["https://openalex.org/I4210151646"]},{"raw_affiliation_string":"Medical Computer Vision and Robotics Lab, University of Toronto, Toronto, ON, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119694990","display_name":"Long V\u00e2n Tran Ha","orcid":null},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]},{"id":"https://openalex.org/I4210151646","display_name":"SGS (Canada)","ror":"https://ror.org/05w5dvb13","country_code":"CA","type":"company","lineage":["https://openalex.org/I4210151646","https://openalex.org/I4210158066"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Long V\u00e2n Tran Ha","raw_affiliation_strings":["Medical Computer Vision and Robotics Laboratory, University of Toronto Mississauga, Mississauga, ON, Canada","Medical Computer Vision and Robotics Lab, University of Toronto, Toronto, ON, Canada"],"affiliations":[{"raw_affiliation_string":"Medical Computer Vision and Robotics Laboratory, University of Toronto Mississauga, Mississauga, ON, Canada","institution_ids":["https://openalex.org/I4210151646"]},{"raw_affiliation_string":"Medical Computer Vision and Robotics Lab, University of Toronto, Toronto, ON, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070006703","display_name":"Joel Davies","orcid":"https://orcid.org/0000-0002-9300-7337"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]},{"id":"https://openalex.org/I4210130843","display_name":"Sinai Health System","ror":"https://ror.org/044790d95","country_code":"CA","type":"healthcare","lineage":["https://openalex.org/I4210130843"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Joel C. Davies","raw_affiliation_strings":["Department of Otolaryngology-Head and Neck Surgery, Sinai Health System, University of Toronto, Toronto, ON, Canada","Department of Otolaryngology - Head and Neck Surgery, Sinai Health System, University of Toronto, Toronto, ON, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Otolaryngology-Head and Neck Surgery, Sinai Health System, University of Toronto, Toronto, ON, Canada","institution_ids":["https://openalex.org/I4210130843","https://openalex.org/I185261750"]},{"raw_affiliation_string":"Department of Otolaryngology - Head and Neck Surgery, Sinai Health System, University of Toronto, Toronto, ON, Canada","institution_ids":["https://openalex.org/I4210130843","https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049319779","display_name":"Eitan Grinspun","orcid":"https://orcid.org/0000-0003-4460-7747"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Eitan Grinspun","raw_affiliation_strings":["Department of Computer Science, University of Toronto, Toronto, ON, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Toronto, Toronto, ON, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044949632","display_name":"L\u00fcder A. Kahrs","orcid":"https://orcid.org/0000-0001-5506-2768"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]},{"id":"https://openalex.org/I4210151646","display_name":"SGS (Canada)","ror":"https://ror.org/05w5dvb13","country_code":"CA","type":"company","lineage":["https://openalex.org/I4210151646","https://openalex.org/I4210158066"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Lueder A. Kahrs","raw_affiliation_strings":["Medical Computer Vision and Robotics Laboratory, University of Toronto Mississauga, Mississauga, ON, Canada","Medical Computer Vision and Robotics Lab, University of Toronto, Toronto, ON, Canada"],"affiliations":[{"raw_affiliation_string":"Medical Computer Vision and Robotics Laboratory, University of Toronto Mississauga, Mississauga, ON, Canada","institution_ids":["https://openalex.org/I4210151646"]},{"raw_affiliation_string":"Medical Computer Vision and Robotics Lab, University of Toronto, Toronto, ON, Canada","institution_ids":["https://openalex.org/I185261750"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5057017654"],"corresponding_institution_ids":["https://openalex.org/I185261750","https://openalex.org/I4210151646"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24678807,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":null,"first_page":"167196","last_page":"167212"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.984499990940094,"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":0.984499990940094,"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":0.8166999816894531},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.757099986076355},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6133000254631042},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.602400004863739},{"id":"https://openalex.org/keywords/head","display_name":"Head (geology)","score":0.5910000205039978},{"id":"https://openalex.org/keywords/3d-pose-estimation","display_name":"3D pose estimation","score":0.508400022983551},{"id":"https://openalex.org/keywords/articulated-body-pose-estimation","display_name":"Articulated body pose estimation","score":0.4564000070095062},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.43140000104904175}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8633999824523926},{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.8166999816894531},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.8062000274658203},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7990000247955322},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.757099986076355},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6133000254631042},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.602400004863739},{"id":"https://openalex.org/C2780312720","wikidata":"https://www.wikidata.org/wiki/Q5689100","display_name":"Head (geology)","level":2,"score":0.5910000205039978},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.508400022983551},{"id":"https://openalex.org/C22100474","wikidata":"https://www.wikidata.org/wiki/Q4800952","display_name":"Articulated body pose estimation","level":4,"score":0.4564000070095062},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.43140000104904175},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.41609999537467957},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.40470001101493835},{"id":"https://openalex.org/C11727466","wikidata":"https://www.wikidata.org/wiki/Q1628157","display_name":"Inpainting","level":3,"score":0.3758000135421753},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3587999939918518},{"id":"https://openalex.org/C195958017","wikidata":"https://www.wikidata.org/wiki/Q1675268","display_name":"Iterative closest point","level":3,"score":0.3580999970436096},{"id":"https://openalex.org/C98907195","wikidata":"https://www.wikidata.org/wiki/Q5428562","display_name":"Facial motion capture","level":5,"score":0.3285999894142151},{"id":"https://openalex.org/C2780549717","wikidata":"https://www.wikidata.org/wiki/Q3409626","display_name":"Human head","level":3,"score":0.3084999918937683},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.2890999913215637},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.287200003862381},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.27900001406669617},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.2694000005722046},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.26010000705718994}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3612890","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3612890","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:c81312a5879c4bf687741f1a8790e4fe","is_oa":true,"landing_page_url":"https://doaj.org/article/c81312a5879c4bf687741f1a8790e4fe","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 167196-167212 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3612890","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3612890","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2799949548","display_name":null,"funder_award_id":"RGPIN-2021-03733","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"}],"funders":[{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W2037814254","https://openalex.org/W2087681821","https://openalex.org/W2111372597","https://openalex.org/W2193145675","https://openalex.org/W2589255576","https://openalex.org/W2724103664","https://openalex.org/W2891485065","https://openalex.org/W2944892540","https://openalex.org/W2949662773","https://openalex.org/W2963163009","https://openalex.org/W2963993755","https://openalex.org/W2991377405","https://openalex.org/W3004542466","https://openalex.org/W3034552680","https://openalex.org/W3035512475","https://openalex.org/W3085402119","https://openalex.org/W3092619908","https://openalex.org/W3107385404","https://openalex.org/W3109496323","https://openalex.org/W3117658046","https://openalex.org/W3126841112","https://openalex.org/W3205044513","https://openalex.org/W3215628224","https://openalex.org/W4206097581","https://openalex.org/W4210719834","https://openalex.org/W4210748481","https://openalex.org/W4285149219","https://openalex.org/W4292899641","https://openalex.org/W4308233968","https://openalex.org/W4310443798","https://openalex.org/W4312497550","https://openalex.org/W4312933868","https://openalex.org/W4313419334","https://openalex.org/W4324290694","https://openalex.org/W4360995323","https://openalex.org/W4385632887","https://openalex.org/W4386076425","https://openalex.org/W4386412367","https://openalex.org/W4390827377","https://openalex.org/W4393253100","https://openalex.org/W4394597120","https://openalex.org/W4394625756","https://openalex.org/W4394625844","https://openalex.org/W4401453309","https://openalex.org/W4402775813","https://openalex.org/W4402917085","https://openalex.org/W4402976435","https://openalex.org/W4403277335","https://openalex.org/W4404436231","https://openalex.org/W4405838310","https://openalex.org/W4408120223","https://openalex.org/W4409261745","https://openalex.org/W4410949897"],"related_works":[],"abstract_inverted_index":{"Face":[0],"occlusion":[1],"often":[2],"makes":[3],"it":[4],"challenging":[5],"to":[6,21,49,109,130,154],"accurately":[7],"detect":[8],"facial":[9,23,86,194],"landmarks":[10,24,69],"and":[11,25,62,156,197],"head":[12,26,77,134,146,149,172,198],"pose.":[13],"In":[14,183],"this":[15],"work,":[16],"we":[17,39,74,88,137,185],"present":[18,186],"a":[19,30,121,144,171,187],"pipeline":[20,106,169],"estimate":[22,75],"pose":[27,78,135,150,173,199],"when":[28],"only":[29],"partial":[31],"face":[32,60,102,158],"is":[33],"visible.":[34],"For":[35,85,98,133],"each":[36,71],"input":[37],"image,":[38],"first":[40],"apply":[41,59],"the":[42,64,76,80,99,111,167,177,191],"Stable":[43],"Diffusion":[44],"Inpainting":[45],"algorithm":[46],"multiple":[47],"times":[48],"generate":[50],"25,":[51],"50,":[52],"or":[53],"100":[54],"inpainted":[55],"images.":[56,159],"We":[57],"then":[58],"trackers":[61],"calculate":[63],"mean":[65],"shape":[66],"of":[67,143,176,193],"extracted":[68],"in":[70,123,180],"image.":[72],"Lastly,":[73],"with":[79,120,148],"iterative":[81],"closest":[82],"point":[83],"method.":[84],"landmarks,":[87],"performed":[89,138],"experiments":[90,139],"on":[91,140],"406":[92],"images":[93],"from":[94,127,152],"publicly":[95],"available":[96],"datasets.":[97],"four":[100],"investigated":[101],"trackers,":[103],"our":[104],"proposed":[105,168],"was":[107],"able":[108],"reduce":[110],"landmark":[112,195],"detection":[113,125,196],"error":[114,126],"by":[115],"at":[116],"least":[117],"2-3":[118],"times,":[119],"reduction":[122],"average":[124],"14.0":[128],"pixels":[129],"3.9":[131],"pixels.":[132],"estimation,":[136],"different":[141],"views":[142],"3D":[145],"model":[147],"ranges":[151],"-60\u00b0":[153],"60\u00b0":[155],"2D":[157],"Across":[160],"more":[161],"than":[162],"3,300":[163],"occluded":[164],"test":[165],"images,":[166],"obtained":[170],"within":[174],"10\u00b0":[175],"ground":[178],"truth":[179],"most":[181],"cases.":[182],"conclusion,":[184],"system":[188],"that":[189],"enhances":[190],"accuracy":[192],"estimation":[200],"under":[201],"large":[202],"occlusions,":[203],"without":[204],"training":[205],"any":[206],"new":[207],"machine":[208],"learning":[209],"models.":[210]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}