{"id":"https://openalex.org/W4313839144","doi":"https://doi.org/10.1109/tbiom.2022.3233769","title":"RGB-D Face Recognition With Identity-Style Disentanglement and Depth Augmentation","display_name":"RGB-D Face Recognition With Identity-Style Disentanglement and Depth Augmentation","publication_year":2023,"publication_date":"2023-01-09","ids":{"openalex":"https://openalex.org/W4313839144","doi":"https://doi.org/10.1109/tbiom.2022.3233769"},"language":"en","primary_location":{"id":"doi:10.1109/tbiom.2022.3233769","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbiom.2022.3233769","pdf_url":null,"source":{"id":"https://openalex.org/S4210209367","display_name":"IEEE Transactions on Biometrics Behavior and Identity Science","issn_l":"2637-6407","issn":["2637-6407"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Biometrics, Behavior, and Identity Science","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/A5028396844","display_name":"Meng-Tzu Chiu","orcid":"https://orcid.org/0000-0002-7733-6536"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Meng-Tzu Chiu","raw_affiliation_strings":["Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan"],"raw_orcid":"https://orcid.org/0000-0002-7733-6536","affiliations":[{"raw_affiliation_string":"Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074022474","display_name":"Hsun-Ying Cheng","orcid":null},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Hsun-Ying Cheng","raw_affiliation_strings":["Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078706898","display_name":"Chien-Yi Wang","orcid":"https://orcid.org/0000-0002-2345-0245"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chien-Yi Wang","raw_affiliation_strings":["Microsoft Artificial Intelligence R&D Center, Microsoft Corporation, Taipei City, Taiwan"],"raw_orcid":"https://orcid.org/0000-0002-2345-0245","affiliations":[{"raw_affiliation_string":"Microsoft Artificial Intelligence R&D Center, Microsoft Corporation, Taipei City, Taiwan","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073849580","display_name":"Shang\u2010Hong Lai","orcid":"https://orcid.org/0000-0002-5092-993X"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Shang-Hong Lai","raw_affiliation_strings":["Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan","Microsoft Artificial Intelligence R&D Center, Microsoft Corporation, Taipei City, Taiwan"],"raw_orcid":"https://orcid.org/0000-0002-5092-993X","affiliations":[{"raw_affiliation_string":"Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I25846049"]},{"raw_affiliation_string":"Microsoft Artificial Intelligence R&D Center, Microsoft Corporation, Taipei City, Taiwan","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5614,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.65981316,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"5","issue":"3","first_page":"334","last_page":"347"},"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/T10057","display_name":"Face and Expression Recognition","score":0.9962999820709229,"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":0.9957000017166138,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8383102416992188},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7710074186325073},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.7006838321685791},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.647701621055603},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.640140175819397},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5982807874679565},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5796988010406494},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5653694868087769},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5317956805229187},{"id":"https://openalex.org/keywords/three-dimensional-face-recognition","display_name":"Three-dimensional face recognition","score":0.44846946001052856},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41690725088119507},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.2688341736793518}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8383102416992188},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7710074186325073},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.7006838321685791},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.647701621055603},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.640140175819397},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5982807874679565},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5796988010406494},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5653694868087769},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5317956805229187},{"id":"https://openalex.org/C88799230","wikidata":"https://www.wikidata.org/wiki/Q3398329","display_name":"Three-dimensional face recognition","level":5,"score":0.44846946001052856},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41690725088119507},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.2688341736793518},{"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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tbiom.2022.3233769","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbiom.2022.3233769","pdf_url":null,"source":{"id":"https://openalex.org/S4210209367","display_name":"IEEE Transactions on Biometrics Behavior and Identity Science","issn_l":"2637-6407","issn":["2637-6407"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Biometrics, Behavior, and Identity Science","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8091812018","display_name":null,"funder_award_id":"110-2634-F-007-019","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"}],"funders":[{"id":"https://openalex.org/F4320322795","display_name":"Ministry of Science and Technology, Taiwan","ror":"https://ror.org/02kv4zf79"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W1509966554","https://openalex.org/W1566413196","https://openalex.org/W1578309724","https://openalex.org/W1901129140","https://openalex.org/W1980257741","https://openalex.org/W1982755836","https://openalex.org/W2107037917","https://openalex.org/W2109647201","https://openalex.org/W2109741874","https://openalex.org/W2137306662","https://openalex.org/W2137659841","https://openalex.org/W2166335841","https://openalex.org/W2194775991","https://openalex.org/W2207409364","https://openalex.org/W2265959009","https://openalex.org/W2512660057","https://openalex.org/W2515770085","https://openalex.org/W2566099512","https://openalex.org/W2612733445","https://openalex.org/W2621864722","https://openalex.org/W2752782242","https://openalex.org/W2770446278","https://openalex.org/W2820458630","https://openalex.org/W2886934227","https://openalex.org/W2904106524","https://openalex.org/W2949662773","https://openalex.org/W2953513570","https://openalex.org/W2961267935","https://openalex.org/W2962827684","https://openalex.org/W2963067184","https://openalex.org/W2963342110","https://openalex.org/W2963839617","https://openalex.org/W2963858339","https://openalex.org/W2963865528","https://openalex.org/W2964296522","https://openalex.org/W2969985801","https://openalex.org/W2984627946","https://openalex.org/W3008039661","https://openalex.org/W3034660477","https://openalex.org/W3035436173","https://openalex.org/W3097003645","https://openalex.org/W3104792420","https://openalex.org/W3109432287","https://openalex.org/W3120254887","https://openalex.org/W3122279806","https://openalex.org/W3175196926","https://openalex.org/W3185372235","https://openalex.org/W3201733951","https://openalex.org/W4210401281","https://openalex.org/W4210586978","https://openalex.org/W4289752563","https://openalex.org/W6630649318","https://openalex.org/W6766047865","https://openalex.org/W6770237082","https://openalex.org/W6774413196"],"related_works":["https://openalex.org/W2166031825","https://openalex.org/W2918845005","https://openalex.org/W2040482211","https://openalex.org/W2058325696","https://openalex.org/W325114128","https://openalex.org/W2185537520","https://openalex.org/W3108145925","https://openalex.org/W4387163326","https://openalex.org/W1517271056","https://openalex.org/W2985118265"],"abstract_inverted_index":{"Deep":[0],"learning":[1],"approaches":[2],"achieve":[3],"highly":[4],"accurate":[5,88],"face":[6,14,19,29,38,61,80,89,99,122,149,156,165,181,189,205],"recognition":[7,62,100,106,111,123,166,190],"by":[8,82],"training":[9,162],"the":[10,33,48,59,133,184,194],"models":[11,56],"with":[12,43,183,207],"huge":[13],"image":[15,20,150],"datasets.":[16],"Unlike":[17],"2D":[18,148],"datasets,":[21],"there":[22],"is":[23,66,94,129,142,159],"a":[24,67,95,108,125,146,153],"lack":[25],"of":[26],"large":[27,147,154],"3D":[28,37,204],"datasets":[30,39,206],"available":[31],"to":[32,47,57,131,144,152],"public.":[34],"Existing":[35],"public":[36,203],"were":[40],"usually":[41],"collected":[42],"few":[44],"subjects,":[45],"leading":[46],"over-fitting":[49],"problem.":[50],"This":[51],"paper":[52],"proposes":[53],"two":[54],"CNN":[55],"improve":[58],"RGB-D":[60,98,155,164],"task.":[63],"The":[64,92],"first":[65],"segmentation-aware":[68],"depth":[69,76,109,178,195],"estimation":[70],"network,":[71],"called":[72],"DepthNet,":[73],"which":[74,158],"estimates":[75],"maps":[77,179],"from":[78,180],"RGB":[79,105],"images":[81,182],"exploiting":[83],"semantic":[84],"segmentation":[85,116,185],"for":[86,161],"more":[87,176],"region":[90],"localization.":[91],"other":[93],"novel":[96],"segmentation-guided":[97],"model":[101,191],"that":[102,172],"contains":[103],"an":[104,114],"branch,":[107,112],"map":[110,196],"and":[113,138,197],"auxiliary":[115],"mask":[117],"branch.":[118],"In":[119],"our":[120,163],"multi-modality":[121,188],"model,":[124],"feature":[126,134],"disentanglement":[127],"scheme":[128],"employed":[130],"factorize":[132],"representation":[135],"into":[136],"identity-related":[137],"style-related":[139],"components.":[140],"DepthNet":[141,173],"applied":[143],"augment":[145],"dataset":[151],"dataset,":[157],"used":[160],"model.":[167],"Our":[168,187],"experimental":[169],"results":[170],"show":[171],"can":[174],"produce":[175],"reliable":[177],"mask.":[186],"fully":[192],"exploits":[193],"outperforms":[198],"state-of-the-art":[199],"methods":[200],"on":[201],"several":[202],"challenging":[208],"variations.":[209]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}