{"id":"https://openalex.org/W2890470722","doi":"https://doi.org/10.1109/icip.2018.8451363","title":"Mixture of Deep Regression Networks for Head Pose Estimation","display_name":"Mixture of Deep Regression Networks for Head Pose Estimation","publication_year":2018,"publication_date":"2018-09-07","ids":{"openalex":"https://openalex.org/W2890470722","doi":"https://doi.org/10.1109/icip.2018.8451363","mag":"2890470722"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2018.8451363","is_oa":false,"landing_page_url":"http://doi.org/10.1109/icip.2018.8451363","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th IEEE International Conference on Image Processing (ICIP)","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/A5051908632","display_name":"Yangguang Huang","orcid":"https://orcid.org/0000-0003-4870-6873"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yangguang Huang","raw_affiliation_strings":["University of Electronic science and technology of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic science and technology of China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004994916","display_name":"Lili Pan","orcid":"https://orcid.org/0000-0003-3903-071X"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lili Pan","raw_affiliation_strings":["University of Electronic science and technology of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic science and technology of China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101913040","display_name":"Yali Zheng","orcid":"https://orcid.org/0000-0002-2906-7984"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yali Zheng","raw_affiliation_strings":["University of Electronic science and technology of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic science and technology of China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100660295","display_name":"Mei Xie","orcid":"https://orcid.org/0000-0001-5605-8867"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mei Xie","raw_affiliation_strings":["University of Electronic science and technology of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic science and technology of China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":0.424,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.67701852,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"11","issue":null,"first_page":"4093","last_page":"4097"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9995999932289124,"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":0.9995999932289124,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9934999942779541,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9884999990463257,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/regression","display_name":"Regression","score":0.6629739999771118},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6233582496643066},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6093341708183289},{"id":"https://openalex.org/keywords/head","display_name":"Head (geology)","score":0.604480504989624},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.5941649675369263},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.5514180660247803},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4599963128566742},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.38299858570098877},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3353661596775055},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.312871515750885},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2206292748451233},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.15967974066734314},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12889966368675232}],"concepts":[{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.6629739999771118},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6233582496643066},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6093341708183289},{"id":"https://openalex.org/C2780312720","wikidata":"https://www.wikidata.org/wiki/Q5689100","display_name":"Head (geology)","level":2,"score":0.604480504989624},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5941649675369263},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.5514180660247803},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4599963128566742},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.38299858570098877},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3353661596775055},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.312871515750885},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2206292748451233},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.15967974066734314},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12889966368675232},{"id":"https://openalex.org/C114793014","wikidata":"https://www.wikidata.org/wiki/Q52109","display_name":"Geomorphology","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2018.8451363","is_oa":false,"landing_page_url":"http://doi.org/10.1109/icip.2018.8451363","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th IEEE International Conference on Image Processing (ICIP)","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":19,"referenced_works":["https://openalex.org/W273955616","https://openalex.org/W1974744233","https://openalex.org/W1982214249","https://openalex.org/W2008627340","https://openalex.org/W2022652211","https://openalex.org/W2047875689","https://openalex.org/W2070076962","https://openalex.org/W2079956894","https://openalex.org/W2100495367","https://openalex.org/W2105899846","https://openalex.org/W2137226992","https://openalex.org/W2147575376","https://openalex.org/W2213673037","https://openalex.org/W2291445757","https://openalex.org/W2293298207","https://openalex.org/W6610017368","https://openalex.org/W6652404702","https://openalex.org/W6676086432","https://openalex.org/W6680532697"],"related_works":["https://openalex.org/W2172272445","https://openalex.org/W4289356671","https://openalex.org/W2389155397","https://openalex.org/W2165884543","https://openalex.org/W2312753042","https://openalex.org/W3186837933","https://openalex.org/W2368989808","https://openalex.org/W2034959125","https://openalex.org/W2355687852","https://openalex.org/W3174513558"],"abstract_inverted_index":{"Accurate":[0],"and":[1,101,120],"robust":[2,103],"head":[3,25,71],"pose":[4,26,72],"estimation":[5],"is":[6],"a":[7,65],"challenging":[8],"computer":[9],"vision":[10],"task.":[11],"In":[12],"most":[13],"existing":[14],"methods,":[15],"single-modal":[16,51],"RGB":[17],"or":[18],"depth":[19],"images":[20],"are":[21,34,41,50],"directly":[22],"used":[23],"for":[24,70,86],"estimation.":[27],"The":[28],"obvious":[29],"drawbacks":[30],"of":[31,76,125],"these":[32],"methods":[33],"two":[35],"fold:":[36],"(1)":[37],"Traditional":[38],"shallow":[39],"models":[40],"not":[42],"good":[43,84],"at":[44],"learning":[45],"representative":[46],"features.":[47],"(2)":[48],"They":[49],"approaches,":[52],"resulting":[53],"in":[54,60,110],"sensitivity":[55],"to":[56,89,97,104],"noise.":[57],"As":[58],"such,":[59],"this":[61],"work":[62],"we":[63],"propose":[64],"novel":[66],"multi-modal":[67],"regression":[68,78],"model":[69],"estimation,":[73],"named":[74],"mixture":[75],"deep":[77],"networks":[79],"(MoDRN).":[80],"It":[81],"only":[82],"uses":[83],"examples":[85],"one":[87],"modality":[88],"learn":[90],"sub-network":[91],"parameters.":[92],"Thus,":[93],"the":[94,123],"sub-networks":[95],"tend":[96],"be":[98],"better":[99],"trained":[100],"more":[102],"noise,":[105],"making":[106],"significant":[107],"improved":[108],"performance":[109],"their":[111],"combination.":[112],"Experiments":[113],"on":[114],"public":[115],"datasets":[116],"such":[117],"as":[118],"BIWI":[119],"BU-3DFE":[121],"show":[122],"effectiveness":[124],"our":[126],"approach.":[127]},"counts_by_year":[{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}