{"id":"https://openalex.org/W4391855168","doi":"https://doi.org/10.1109/tnnls.2024.3360712","title":"MH6D: Multi-Hypothesis Consistency Learning for Category-Level 6-D Object Pose Estimation","display_name":"MH6D: Multi-Hypothesis Consistency Learning for Category-Level 6-D Object Pose Estimation","publication_year":2024,"publication_date":"2024-02-13","ids":{"openalex":"https://openalex.org/W4391855168","doi":"https://doi.org/10.1109/tnnls.2024.3360712","pmid":"https://pubmed.ncbi.nlm.nih.gov/38356214"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2024.3360712","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3360712","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5108049455","display_name":"Jian Liu","orcid":"https://orcid.org/0000-0003-0604-8024"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]},{"id":"https://openalex.org/I177877127","display_name":"The University of Western Australia","ror":"https://ror.org/047272k79","country_code":"AU","type":"education","lineage":["https://openalex.org/I177877127"]}],"countries":["AU","CN"],"is_corresponding":false,"raw_author_name":"Jian Liu","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China","Department of Computer Science, The University of Western Australia, Perth, WA, Australia"],"raw_orcid":"https://orcid.org/0000-0003-0604-8024","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]},{"raw_affiliation_string":"Department of Computer Science, The University of Western Australia, Perth, WA, Australia","institution_ids":["https://openalex.org/I177877127"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100637917","display_name":"Wei Sun","orcid":"https://orcid.org/0000-0002-8644-2998"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Sun","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China","Shenzhen Research Institute, Hunan University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-8644-2998","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]},{"raw_affiliation_string":"Shenzhen Research Institute, Hunan University, Shenzhen, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038350490","display_name":"Chongpei Liu","orcid":"https://orcid.org/0000-0002-5656-2622"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chongpei Liu","raw_affiliation_strings":["College of Electrical and Information Engineering and the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-5656-2622","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering and the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112361483","display_name":"Hui Yang","orcid":"https://orcid.org/0009-0005-2648-9566"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Yang","raw_affiliation_strings":["College of Electrical and Information Engineering and the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering and the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100399141","display_name":"Xing Zhang","orcid":"https://orcid.org/0000-0002-7639-2704"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xing Zhang","raw_affiliation_strings":["College of Electrical and Information Engineering and the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-7639-2704","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering and the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089986388","display_name":"Ajmal Mian","orcid":"https://orcid.org/0000-0002-5206-3842"},"institutions":[{"id":"https://openalex.org/I177877127","display_name":"The University of Western Australia","ror":"https://ror.org/047272k79","country_code":"AU","type":"education","lineage":["https://openalex.org/I177877127"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Ajmal Mian","raw_affiliation_strings":["Department of Computer Science, The University of Western Australia, Perth, WA, Australia"],"raw_orcid":"https://orcid.org/0000-0002-5206-3842","affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Western Australia, Perth, WA, Australia","institution_ids":["https://openalex.org/I177877127"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.952,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.95662644,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"36","issue":"3","first_page":"4820","last_page":"4833"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10653","display_name":"Robot Manipulation and Learning","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10812","display_name":"Human Pose and Action Recognition","score":0.9664999842643738,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9394999742507935,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.7893326878547668},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7186520099639893},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7176958322525024},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6335187554359436},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.621732234954834},{"id":"https://openalex.org/keywords/3d-pose-estimation","display_name":"3D pose estimation","score":0.5531394481658936},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5268282294273376},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5263378024101257},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5138445496559143},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4533126652240753},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34736934304237366},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3279690146446228},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13519570231437683}],"concepts":[{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.7893326878547668},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7186520099639893},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7176958322525024},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6335187554359436},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.621732234954834},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.5531394481658936},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5268282294273376},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5263378024101257},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5138445496559143},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4533126652240753},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34736934304237366},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3279690146446228},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13519570231437683},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tnnls.2024.3360712","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3360712","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:38356214","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38356214","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null},{"id":"pmh:oai:pure.atira.dk:publications/315a6ce0-df30-4692-85bf-f9c00e755a7f","is_oa":false,"landing_page_url":"https://research-repository.uwa.edu.au/en/publications/315a6ce0-df30-4692-85bf-f9c00e755a7f","pdf_url":null,"source":{"id":"https://openalex.org/S4306402523","display_name":"UWA Profiles and Research Repository (University of Western Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I177877127","host_organization_name":"The University of Western Australia","host_organization_lineage":["https://openalex.org/I177877127"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Liu, J, Sun, W, Liu, C, Yang, H, Zhang, X & Mian, A 2025, 'MH6D : Multi-Hypothesis Consistency Learning for Category-Level 6-D Object Pose Estimation', IEEE Transactions on Neural Networks and Learning Systems, vol. 36, no. 3, pp. 4820-4833. https://doi.org/10.1109/TNNLS.2024.3360712","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.4000000059604645}],"awards":[{"id":"https://openalex.org/G3408348127","display_name":null,"funder_award_id":"U22A2059","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5069660017","display_name":null,"funder_award_id":"202306130074","funder_id":"https://openalex.org/F4320322725","funder_display_name":"China Scholarship Council"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W2560023338","https://openalex.org/W2963150697","https://openalex.org/W2963177347","https://openalex.org/W2963627347","https://openalex.org/W2963892972","https://openalex.org/W2964014140","https://openalex.org/W2964054038","https://openalex.org/W2964056579","https://openalex.org/W2964249569","https://openalex.org/W3034986117","https://openalex.org/W3093644825","https://openalex.org/W3107992529","https://openalex.org/W3113383835","https://openalex.org/W3163945288","https://openalex.org/W3175584021","https://openalex.org/W3179923621","https://openalex.org/W3193686508","https://openalex.org/W3202459445","https://openalex.org/W3202538459","https://openalex.org/W3203218344","https://openalex.org/W3206934897","https://openalex.org/W3207749834","https://openalex.org/W3214778407","https://openalex.org/W4200531006","https://openalex.org/W4220980185","https://openalex.org/W4223499953","https://openalex.org/W4225463624","https://openalex.org/W4226321491","https://openalex.org/W4226391004","https://openalex.org/W4226409831","https://openalex.org/W4280589974","https://openalex.org/W4283808280","https://openalex.org/W4285233964","https://openalex.org/W4312107217","https://openalex.org/W4312249545","https://openalex.org/W4312282854","https://openalex.org/W4312296985","https://openalex.org/W4312604533","https://openalex.org/W4312818087","https://openalex.org/W4312877043","https://openalex.org/W4313176116","https://openalex.org/W4316669391","https://openalex.org/W4321033239","https://openalex.org/W4384201319","https://openalex.org/W6739778489","https://openalex.org/W6810937846","https://openalex.org/W6839186193","https://openalex.org/W6848159663"],"related_works":["https://openalex.org/W4320086129","https://openalex.org/W4253893311","https://openalex.org/W3089306886","https://openalex.org/W2113785214","https://openalex.org/W3201205132","https://openalex.org/W2798721181","https://openalex.org/W4387967917","https://openalex.org/W4312694060","https://openalex.org/W4386075737","https://openalex.org/W4382141741"],"abstract_inverted_index":{"Six-degree-of-freedom":[0],"(6DoF)":[1],"object":[2,78,154],"pose":[3,18,79,116,132],"estimation":[4,19,80,133],"is":[5,145,239],"a":[6,29,88,169],"crucial":[7],"task":[8],"for":[9,75],"virtual":[10],"reality":[11],"and":[12,55,101,139,158,162,178,203,205],"accurate":[13],"robotic":[14],"manipulation.":[15],"Category-level":[16],"6DoF":[17],"has":[20],"recently":[21],"become":[22],"popular":[23],"as":[24],"it":[25],"improves":[26],"generalization":[27,211],"to":[28,59,61,106,148,185,208],"complete":[30],"category":[31],"of":[32,50,97,104,213],"objects.":[33,63],"However,":[34],"current":[35],"methods":[36,230],"focus":[37],"on":[38,47,123,217],"data-driven":[39,229],"differential":[40],"learning,":[41],"which":[42],"makes":[43],"them":[44],"highly":[45],"dependent":[46],"the":[48,51,94,108,124,150,160,176,179,210],"quality":[49],"real-world":[52,83,206,235],"labeled":[53],"data":[54,197,202],"limits":[56],"their":[57],"ability":[58,212],"generalize":[60],"unseen":[62],"To":[64],"address":[65],"this":[66],"problem,":[67],"we":[68,167],"propose":[69,168],"multi-hypothesis":[70],"(MH)":[71],"consistency":[72,90,188],"learning":[73,91],"(MH6D)":[74],"category-level":[76,130],"6-D":[77,131,153],"without":[81,232],"using":[82,233],"training":[84,196],"data.":[85,236],"MH6D":[86,184,222],"uses":[87],"parallel":[89,122],"structure,":[92],"alleviating":[93],"uncertainty":[95],"problem":[96],"single-shot":[98],"feature":[99,141],"extraction":[100],"promoting":[102],"self-adaptation":[103],"domain":[105,110],"reduce":[107],"synthetic-to-real":[109],"gap.":[111],"Specifically,":[112],"three":[113,151],"randomly":[114],"sampled":[115],"transformations":[117],"are":[118],"first":[119],"performed":[120],"in":[121],"input":[125],"point":[126],"cloud.":[127],"An":[128],"attention-guided":[129],"network":[134],"with":[135],"channel":[136],"attention":[137],"(CA)":[138],"global":[140,161],"cross-attention":[142],"(GFCA)":[143],"modules":[144],"then":[146],"proposed":[147],"estimate":[149],"hypothesized":[152],"poses":[155],"by":[156],"extracting":[157],"fusing":[159],"local":[163],"features":[164],"effectively.":[165],"Finally,":[166],"novel":[170],"loss":[171],"function":[172],"that":[173,221],"considers":[174],"both":[175],"process":[177],"final":[180],"result":[181],"information":[182],"allowing":[183],"perform":[186],"robust":[187],"learning.":[189],"We":[190],"conduct":[191],"experiments":[192,216],"under":[193],"two":[194],"different":[195],"settings":[198],"(i.e.,":[199],"only":[200],"synthetic":[201,204],"data)":[207],"verify":[209],"MH6D.":[214],"Extensive":[215],"benchmark":[218],"datasets":[219],"demonstrate":[220],"achieves":[223],"state-of-the-art":[224],"(SOTA)":[225],"performance,":[226],"outperforming":[227],"most":[228],"even":[231],"any":[234],"The":[237],"code":[238],"available":[240],"at":[241],"https://github.com/CNJianLiu/MH6D.":[242]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":4}],"updated_date":"2026-07-02T09:51:11.867554","created_date":"2025-10-10T00:00:00"}