{"id":"https://openalex.org/W4382365515","doi":"https://doi.org/10.1109/tcsvt.2023.3290617","title":"NVR-Net: Normal Vector Guided Regression Network for Disentangled 6D Pose Estimation","display_name":"NVR-Net: Normal Vector Guided Regression Network for Disentangled 6D Pose Estimation","publication_year":2023,"publication_date":"2023-06-28","ids":{"openalex":"https://openalex.org/W4382365515","doi":"https://doi.org/10.1109/tcsvt.2023.3290617"},"language":"en","primary_location":{"id":"doi:10.1109/tcsvt.2023.3290617","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2023.3290617","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"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 Circuits and Systems for Video Technology","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/A5054011056","display_name":"Guangkun Feng","orcid":"https://orcid.org/0000-0003-1949-5958"},"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":"Guangkun Feng","raw_affiliation_strings":["Ministry of Education Key Laboratory of Precision Opto-Mechatronics Technology, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Ministry of Education Key Laboratory of Precision Opto-Mechatronics Technology, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033640729","display_name":"Ting-Bing Xu","orcid":"https://orcid.org/0000-0002-0835-5792"},"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":"Ting-Bing Xu","raw_affiliation_strings":["Ministry of Education Key Laboratory of Precision Opto-Mechatronics Technology, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Ministry of Education Key Laboratory of Precision Opto-Mechatronics Technology, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052682349","display_name":"Fulin Liu","orcid":"https://orcid.org/0000-0002-2033-2040"},"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":"Fulin Liu","raw_affiliation_strings":["Ministry of Education Key Laboratory of Precision Opto-Mechatronics Technology, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Ministry of Education Key Laboratory of Precision Opto-Mechatronics Technology, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088775357","display_name":"Mingkun Liu","orcid":"https://orcid.org/0000-0002-5550-7699"},"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":"Mingkun Liu","raw_affiliation_strings":["Ministry of Education Key Laboratory of Precision Opto-Mechatronics Technology, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Ministry of Education Key Laboratory of Precision Opto-Mechatronics Technology, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075939703","display_name":"Zhenzhong Wei","orcid":"https://orcid.org/0000-0002-8925-9259"},"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":"Zhenzhong Wei","raw_affiliation_strings":["Ministry of Education Key Laboratory of Precision Opto-Mechatronics Technology, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Ministry of Education Key Laboratory of Precision Opto-Mechatronics Technology, School of Instrumentation and Optoelectronic Engineering, 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/A5054011056"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":14.855,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.98451689,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"34","issue":"2","first_page":"1098","last_page":"1113"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9973000288009644,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9959999918937683,"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/pose","display_name":"Pose","score":0.7818500995635986},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7733014822006226},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5986925959587097},{"id":"https://openalex.org/keywords/rotation","display_name":"Rotation (mathematics)","score":0.5769430994987488},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5686958432197571},{"id":"https://openalex.org/keywords/translation","display_name":"Translation (biology)","score":0.5265707969665527},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5231448411941528},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.4947313964366913},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4663488268852234},{"id":"https://openalex.org/keywords/3d-pose-estimation","display_name":"3D pose estimation","score":0.4394654333591461},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.4235069453716278},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.37382426857948303}],"concepts":[{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.7818500995635986},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7733014822006226},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5986925959587097},{"id":"https://openalex.org/C74050887","wikidata":"https://www.wikidata.org/wiki/Q848368","display_name":"Rotation (mathematics)","level":2,"score":0.5769430994987488},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5686958432197571},{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.5265707969665527},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5231448411941528},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.4947313964366913},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4663488268852234},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.4394654333591461},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.4235069453716278},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37382426857948303},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C105580179","wikidata":"https://www.wikidata.org/wiki/Q188928","display_name":"Messenger RNA","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsvt.2023.3290617","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2023.3290617","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"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 Circuits and Systems for Video Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6150355809","display_name":null,"funder_award_id":"52127809","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8488654168","display_name":null,"funder_award_id":"51625501","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":72,"referenced_works":["https://openalex.org/W132147841","https://openalex.org/W196239571","https://openalex.org/W639708223","https://openalex.org/W1526868886","https://openalex.org/W1899309388","https://openalex.org/W1905829557","https://openalex.org/W1984382664","https://openalex.org/W2036273537","https://openalex.org/W2063005413","https://openalex.org/W2085261163","https://openalex.org/W2101199297","https://openalex.org/W2124907686","https://openalex.org/W2151103935","https://openalex.org/W2161168419","https://openalex.org/W2162132961","https://openalex.org/W2165919662","https://openalex.org/W2186094539","https://openalex.org/W2193145675","https://openalex.org/W2194775991","https://openalex.org/W2200124539","https://openalex.org/W2342976462","https://openalex.org/W2344474200","https://openalex.org/W2556455135","https://openalex.org/W2570343428","https://openalex.org/W2604236302","https://openalex.org/W2605102758","https://openalex.org/W2768879211","https://openalex.org/W2797394534","https://openalex.org/W2799123546","https://openalex.org/W2895410314","https://openalex.org/W2895439318","https://openalex.org/W2911784130","https://openalex.org/W2949924544","https://openalex.org/W2950921159","https://openalex.org/W2962783853","https://openalex.org/W2962809185","https://openalex.org/W2963150697","https://openalex.org/W2963177347","https://openalex.org/W2963188159","https://openalex.org/W2963288137","https://openalex.org/W2963856988","https://openalex.org/W2964002966","https://openalex.org/W2964249569","https://openalex.org/W2981378444","https://openalex.org/W2981857055","https://openalex.org/W2987672160","https://openalex.org/W2989915422","https://openalex.org/W3009516594","https://openalex.org/W3021282624","https://openalex.org/W3027201070","https://openalex.org/W3034268164","https://openalex.org/W3034573608","https://openalex.org/W3034971973","https://openalex.org/W3035217469","https://openalex.org/W3035355652","https://openalex.org/W3089306886","https://openalex.org/W3091766791","https://openalex.org/W3092663126","https://openalex.org/W3092774272","https://openalex.org/W3101338131","https://openalex.org/W3106250896","https://openalex.org/W3113383835","https://openalex.org/W3128632815","https://openalex.org/W3130138602","https://openalex.org/W3177069133","https://openalex.org/W4205274304","https://openalex.org/W4285233964","https://openalex.org/W4293584584","https://openalex.org/W6607981818","https://openalex.org/W6750227808","https://openalex.org/W6754437493","https://openalex.org/W6785749668"],"related_works":["https://openalex.org/W4253893311","https://openalex.org/W2798721181","https://openalex.org/W3201205132","https://openalex.org/W4287600488","https://openalex.org/W4312694060","https://openalex.org/W4281696776","https://openalex.org/W4318148659","https://openalex.org/W4387967917","https://openalex.org/W4299867837","https://openalex.org/W2951583186"],"abstract_inverted_index":{"Monocular":[0],"6D":[1,80,199],"pose":[2,81,103,200],"estimation":[3],"for":[4,25,50,102],"objects":[5],"is":[6,13],"an":[7,206],"essential":[8],"but":[9,55],"challenging":[10],"task":[11],"that":[12,175],"commonly":[14],"applied":[15],"in":[16,35,60,209],"computer":[17],"vision":[18],"and":[19,52,142,184,190],"robotics.":[20],"Existing":[21],"two-stage":[22],"methods":[23,42,180],"solve":[24,49],"rotations":[26,51,141],"with":[27],"Perspective-n-Point":[28],"(PnP),":[29],"which":[30],"still":[31],"incorporates":[32],"translations,":[33],"resulting":[34],"accuracy":[36,183],"degeneration.":[37],"In":[38,63],"contrast,":[39],"direct":[40],"regression":[41],"adopt":[43],"Convolutional":[44],"Neural":[45],"Networks":[46],"(CNNs)":[47],"to":[48,76,115,127],"translations":[53,143],"jointly":[54],"suffer":[56],"from":[57,82,119,145,153],"performance":[58],"gaps":[59],"rotation":[61,118,182],"accuracy.":[62],"this":[64],"article,":[65],"we":[66,95,123,148],"propose":[67,149],"a":[68,83,97,125,129,150,163,202],"novel":[69,98,151],"Normal":[70,154],"Vector":[71],"guided":[72],"Regression":[73],"Network":[74],"(NVR-Net)":[75],"directly":[77],"regress":[78],"the":[79,88,134,146,160,186,198],"single":[84,203],"RGB":[85,207],"image":[86,208],"under":[87,159],"guidance":[89],"of":[90,107,111,133,162,201],"3D":[91,112],"normal":[92,113],"vectors.":[93],"Specifically,":[94],"design":[96],"Orientation-Aware":[99],"Feature":[100],"(OAF)":[101],"estimation.":[104,121],"It":[105],"consists":[106],"two":[108],"corresponding":[109],"sets":[110],"vectors":[114],"thoroughly":[116],"disentangle":[117],"translation":[120],"Then,":[122],"introduce":[124],"CNN":[126],"predict":[128],"dense":[130],"pixelwise":[131],"representation":[132],"OAF":[135],"without":[136],"viewpoint":[137],"ambiguity.":[138],"To":[139],"estimate":[140,197],"individually":[144],"OAF,":[147],"Pose":[152],"Vectors":[155],"(PNV)":[156],"head":[157],"networks":[158],"instruction":[161],"differentiable":[164],"closed-form":[165],"solution.":[166],"Finally,":[167],"extensive":[168],"experiments":[169],"on":[170,181],"three":[171],"common":[172],"benchmarks":[173],"demonstrate":[174],"our":[176,194],"approach":[177],"outperforms":[178],"state-of-the-art":[179],"removes":[185],"gap":[187],"between":[188],"indirect":[189],"end-to-end":[191],"methods.":[192],"Moreover,":[193],"method":[195],"can":[196],"object":[204],"within":[205],"real-time.":[210]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3}],"updated_date":"2026-04-06T07:47:59.780226","created_date":"2025-10-10T00:00:00"}