{"id":"https://openalex.org/W6907630032","doi":"https://doi.org/10.2312/stag.20241335","title":"FAST GDRNPP: Improving the Speed of State-of-the-Art 6D Object Pose Estimation","display_name":"FAST GDRNPP: Improving the Speed of State-of-the-Art 6D Object Pose Estimation","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W6907630032","doi":"https://doi.org/10.2312/stag.20241335"},"language":"en","primary_location":{"id":"pmh:oai:publica.fraunhofer.de:publica/479123","is_oa":true,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/479123","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"},"type":"conference-paper","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://publica.fraunhofer.de/handle/publica/479123","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"P\u00f6llabauer, Thomas","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"P\u00f6llabauer, Thomas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Pramod, Ashwin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pramod, Ashwin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Knauthe, Volker","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Knauthe, Volker","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Wahl, Michael","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wahl, Michael","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.56268657,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9769999980926514,"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":0.9769999980926514,"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":0.004399999976158142,"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":0.00430000014603138,"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":0.8051999807357788},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6657000184059143},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5701000094413757},{"id":"https://openalex.org/keywords/3d-pose-estimation","display_name":"3D pose estimation","score":0.5095999836921692},{"id":"https://openalex.org/keywords/rotation","display_name":"Rotation (mathematics)","score":0.4578000009059906},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.40560001134872437},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.39629998803138733},{"id":"https://openalex.org/keywords/translation","display_name":"Translation (biology)","score":0.38929998874664307}],"concepts":[{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.8051999807357788},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7470999956130981},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7312999963760376},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6657000184059143},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6123999953269958},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5701000094413757},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.5095999836921692},{"id":"https://openalex.org/C74050887","wikidata":"https://www.wikidata.org/wiki/Q848368","display_name":"Rotation (mathematics)","level":2,"score":0.4578000009059906},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4244999885559082},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.40560001134872437},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.39629998803138733},{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.38929998874664307},{"id":"https://openalex.org/C22100474","wikidata":"https://www.wikidata.org/wiki/Q4800952","display_name":"Articulated body pose estimation","level":4,"score":0.35249999165534973},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.3506999909877777},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.34220001101493835},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.32339999079704285},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.29600000381469727},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.2870999872684479},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.27320000529289246},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27149999141693115}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:publica.fraunhofer.de:publica/479123","is_oa":true,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/479123","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"},{"id":"doi:10.2312/stag.20241335","is_oa":true,"landing_page_url":"https://doi.org/10.2312/stag.20241335","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"ConferencePaper"}],"best_oa_location":{"id":"pmh:oai:publica.fraunhofer.de:publica/479123","is_oa":true,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/479123","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.4832756519317627,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"6D":[0,170],"object":[1,13],"pose":[2],"estimation":[3],"involves":[4],"determining":[5],"the":[6,65,76,97,136,143,166],"three-dimensional":[7],"translation":[8],"and":[9,17,43,49,60,69,100,109,115,157],"rotation":[10],"of":[11,27,78,169],"an":[12],"within":[14],"a":[15,20,79,121,126],"scene":[16],"relative":[18],"to":[19,95,117,125,142,154],"chosen":[21],"coordinate":[22],"system.":[23],"This":[24,150],"problem":[25],"is":[26],"particular":[28],"interest":[29],"for":[30,53],"many":[31],"practical":[32,158],"applications":[33,159],"in":[34,160,175],"industrial":[35,162],"tasks":[36],"such":[37],"as":[38],"quality":[39],"control,":[40],"bin":[41],"picking,":[42],"robotic":[44],"manipulation,":[45],"where":[46],"both":[47,58],"speed":[48,77],"accuracy":[50,68,140],"are":[51],"critical":[52],"real-world":[54,176],"deployment.":[55],"Current":[56],"models,":[57],"classical":[59],"deep-learning-based,":[61],"often":[62],"struggle":[63],"with":[64],"trade-off":[66],"between":[67],"latency.":[70],"Our":[71,132],"research":[72],"focuses":[73],"on":[74],"enhancing":[75,165],"prominent":[80],"state-of-the-art":[81,144],"deep":[82],"learning":[83],"model,":[84],"GDRNPP,":[85],"while":[86,145],"keeping":[87],"its":[88],"high":[89],"accuracy.":[90],"We":[91],"employ":[92],"several":[93],"techniques":[94,105],"reduce":[96],"model":[98,124],"size":[99],"improve":[101],"inference":[102,148],"time.":[103,149],"These":[104],"include":[106],"using":[107],"smaller":[108],"quicker":[110],"backbones,":[111],"pruning":[112],"unnecessary":[113],"parameters,":[114],"distillation":[116],"transfer":[118],"knowledge":[119],"from":[120],"large,":[122],"high-performing":[123],"smaller,":[127],"more":[128,155],"efficient":[129,156],"student":[130],"model.":[131],"findings":[133],"demonstrate":[134],"that":[135],"proposed":[137],"configuration":[138],"maintains":[139],"comparable":[141],"significantly":[146],"improving":[147],"advancement":[151],"could":[152],"lead":[153],"various":[161],"scenarios,":[163],"thereby":[164],"overall":[167],"applicability":[168],"Object":[171],"Pose":[172],"Estimation":[173],"models":[174],"settings.":[177]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}