{"id":"https://openalex.org/W4391331170","doi":"https://doi.org/10.1109/smc53992.2023.10394339","title":"Improving 6D Object Pose Estimation Based on Semantic Segmentation","display_name":"Improving 6D Object Pose Estimation Based on Semantic Segmentation","publication_year":2023,"publication_date":"2023-10-01","ids":{"openalex":"https://openalex.org/W4391331170","doi":"https://doi.org/10.1109/smc53992.2023.10394339"},"language":"en","primary_location":{"id":"doi:10.1109/smc53992.2023.10394339","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/smc53992.2023.10394339","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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/A5006605583","display_name":"Fang Gao","orcid":"https://orcid.org/0000-0003-1816-5420"},"institutions":[{"id":"https://openalex.org/I150807315","display_name":"Guangxi University","ror":"https://ror.org/02c9qn167","country_code":"CN","type":"education","lineage":["https://openalex.org/I150807315"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Fang Gao","raw_affiliation_strings":["School of Electrical Engineering, Guangxi University,Nanning,China","School of Electrical Engineering, Guangxi University, Nanning, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Guangxi University,Nanning,China","institution_ids":["https://openalex.org/I150807315"]},{"raw_affiliation_string":"School of Electrical Engineering, Guangxi University, Nanning, China","institution_ids":["https://openalex.org/I150807315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028261944","display_name":"Qiujun Li","orcid":null},"institutions":[{"id":"https://openalex.org/I150807315","display_name":"Guangxi University","ror":"https://ror.org/02c9qn167","country_code":"CN","type":"education","lineage":["https://openalex.org/I150807315"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiujun Li","raw_affiliation_strings":["School of Electrical Engineering, Guangxi University,Nanning,China","School of Electrical Engineering, Guangxi University, Nanning, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Guangxi University,Nanning,China","institution_ids":["https://openalex.org/I150807315"]},{"raw_affiliation_string":"School of Electrical Engineering, Guangxi University, Nanning, China","institution_ids":["https://openalex.org/I150807315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113211959","display_name":"Qingyi Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I150807315","display_name":"Guangxi University","ror":"https://ror.org/02c9qn167","country_code":"CN","type":"education","lineage":["https://openalex.org/I150807315"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingyi Sun","raw_affiliation_strings":["School of Electrical Engineering, Guangxi University,Nanning,China","School of Electrical Engineering, Guangxi University, Nanning, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Guangxi University,Nanning,China","institution_ids":["https://openalex.org/I150807315"]},{"raw_affiliation_string":"School of Electrical Engineering, Guangxi University, Nanning, China","institution_ids":["https://openalex.org/I150807315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5006605583"],"corresponding_institution_ids":["https://openalex.org/I150807315"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24552319,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3763","last_page":"3769"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9994999766349792,"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":0.9994999766349792,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.998199999332428,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9882000088691711,"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/computer-science","display_name":"Computer science","score":0.8506191968917847},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7988696694374084},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7899391055107117},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.7605549693107605},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.7300204038619995},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.6551873683929443},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5962164402008057},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5415847897529602},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4837808310985565},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4716847538948059},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4665873646736145},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.43743178248405457},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39500653743743896}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8506191968917847},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7988696694374084},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7899391055107117},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.7605549693107605},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7300204038619995},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.6551873683929443},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5962164402008057},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5415847897529602},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4837808310985565},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4716847538948059},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4665873646736145},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.43743178248405457},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39500653743743896},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc53992.2023.10394339","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/smc53992.2023.10394339","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W132147841","https://openalex.org/W1022526533","https://openalex.org/W1526868886","https://openalex.org/W1909903157","https://openalex.org/W1969868017","https://openalex.org/W1991544872","https://openalex.org/W2011792403","https://openalex.org/W2050966058","https://openalex.org/W2059412355","https://openalex.org/W2083624955","https://openalex.org/W2124386111","https://openalex.org/W2150066425","https://openalex.org/W2200124539","https://openalex.org/W2344474200","https://openalex.org/W2482368135","https://openalex.org/W2488101876","https://openalex.org/W2555618208","https://openalex.org/W2565639579","https://openalex.org/W2604236302","https://openalex.org/W2768879211","https://openalex.org/W2914804813","https://openalex.org/W2962783853","https://openalex.org/W2962888833","https://openalex.org/W2963177347","https://openalex.org/W2963188159","https://openalex.org/W2963756608","https://openalex.org/W2964062501","https://openalex.org/W2964249569","https://openalex.org/W3009516594","https://openalex.org/W3034986117","https://openalex.org/W3035268949","https://openalex.org/W3092774272","https://openalex.org/W3101338131","https://openalex.org/W3110903173","https://openalex.org/W3135435163","https://openalex.org/W3177069133","https://openalex.org/W3179923621","https://openalex.org/W3193676140","https://openalex.org/W4226165416","https://openalex.org/W4236965008"],"related_works":["https://openalex.org/W4320086129","https://openalex.org/W2185902295","https://openalex.org/W2103507220","https://openalex.org/W3144569342","https://openalex.org/W2945274617","https://openalex.org/W4313052709","https://openalex.org/W2022929107","https://openalex.org/W2055202857","https://openalex.org/W80586315","https://openalex.org/W4205800335"],"abstract_inverted_index":{"The":[0],"performance":[1,100],"of":[2,101],"6D":[3],"pose":[4,46,95],"estimation,":[5],"which":[6,49],"is":[7,115],"important":[8],"for":[9,34,94],"scene":[10],"understanding,":[11],"can":[12,25,50],"be":[13],"improved":[14],"by":[15],"more":[16,27,52],"accurate":[17,28],"object":[18],"segmentation.":[19,36],"RGB-D":[20],"data":[21,33,73],"including":[22],"depth":[23],"maps":[24],"provide":[26,51],"position":[29],"information":[30],"than":[31],"RGB":[32],"semantic":[35,54,66],"In":[37],"this":[38],"work,":[39],"we":[40,62],"propose":[41],"a":[42,64,83],"novel":[43],"two-stage":[44],"RGBD-based":[45],"estimation":[47],"network,":[48],"precise":[53],"segmentation":[55,67],"and":[56,80,85,108],"effective":[57],"point":[58,91],"cloud":[59,92],"features.":[60],"Firstly,":[61],"use":[63,82],"lightweight":[65],"head":[68],"to":[69,74,88,117],"process":[70],"the":[71,76,90,99,105,109],"RBG-D":[72],"get":[75],"pixel-level":[77],"clustered":[78],"mask,":[79],"then":[81],"multi-scale":[84],"attention-based":[86],"backbone":[87],"extract":[89],"features":[93],"estimation.":[96],"We":[97],"analyze":[98],"our":[102,113],"network":[103],"on":[104],"YCB-Video":[106],"dataset":[107],"results":[110],"show":[111],"that":[112],"method":[114],"comparable":[116],"current":[118],"state-of-the-art":[119],"methods":[120],"after":[121],"optimization.":[122]},"counts_by_year":[],"updated_date":"2025-12-25T23:11:45.687758","created_date":"2025-10-10T00:00:00"}
