{"id":"https://openalex.org/W7128918499","doi":"https://doi.org/10.1145/3788731.3788738","title":"Auto6D: A unified Framework for Automated 6D Pose Dataset Construction via Real-Sensor Fusion and Physically-Based Simulation","display_name":"Auto6D: A unified Framework for Automated 6D Pose Dataset Construction via Real-Sensor Fusion and Physically-Based Simulation","publication_year":2025,"publication_date":"2025-12-19","ids":{"openalex":"https://openalex.org/W7128918499","doi":"https://doi.org/10.1145/3788731.3788738"},"language":null,"primary_location":{"id":"doi:10.1145/3788731.3788738","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3788731.3788738","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 International Conference on Embodied Intelligence and Large Models","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3788731.3788738","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126018283","display_name":"Xiaochen Yan","orcid":null},"institutions":[{"id":"https://openalex.org/I13591777","display_name":"University of Nottingham Ningbo China","ror":"https://ror.org/03y4dt428","country_code":"CN","type":"education","lineage":["https://openalex.org/I13591777","https://openalex.org/I142263535"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaochen Yan","raw_affiliation_strings":["Ningbo Artificial Intelligence Institute, School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Ningbo, Zhejiang, China"],"raw_orcid":"https://orcid.org/0009-0008-5584-5234","affiliations":[{"raw_affiliation_string":"Ningbo Artificial Intelligence Institute, School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Ningbo, Zhejiang, China","institution_ids":["https://openalex.org/I13591777"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5126014782","display_name":"Genke Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I13591777","display_name":"University of Nottingham Ningbo China","ror":"https://ror.org/03y4dt428","country_code":"CN","type":"education","lineage":["https://openalex.org/I13591777","https://openalex.org/I142263535"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Genke Yang","raw_affiliation_strings":["Ningbo Artificial Intelligence Institute, School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Ningbo, Zhejiang, China"],"raw_orcid":"https://orcid.org/0000-0003-3492-0211","affiliations":[{"raw_affiliation_string":"Ningbo Artificial Intelligence Institute, School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Ningbo, Zhejiang, China","institution_ids":["https://openalex.org/I13591777"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5126018283"],"corresponding_institution_ids":["https://openalex.org/I13591777"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.67732742,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"44","last_page":"50"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.7325999736785889,"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":0.7325999736785889,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.08649999648332596,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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":0.03889999911189079,"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/pipeline","display_name":"Pipeline (software)","score":0.7153000235557556},{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.6809999942779541},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5827000141143799},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.5726000070571899},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.5511999726295471},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5274999737739563},{"id":"https://openalex.org/keywords/pipeline-transport","display_name":"Pipeline transport","score":0.44859999418258667},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4016000032424927}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7354000210762024},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.7153000235557556},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.6809999942779541},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5827000141143799},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.5726000070571899},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5684999823570251},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.5511999726295471},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5274999737739563},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.45249998569488525},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.44859999418258667},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4016000032424927},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.3734999895095825},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37119999527931213},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.35830000042915344},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.34290000796318054},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.323199987411499},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3012999892234802},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.2842999994754791},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.27790001034736633},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.2759999930858612},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.25529998540878296},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.25290000438690186},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2515000104904175}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3788731.3788738","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3788731.3788738","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 International Conference on Embodied Intelligence and Large Models","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3788731.3788738","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3788731.3788738","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 International Conference on Embodied Intelligence and Large Models","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.6453869342803955}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W62794737","https://openalex.org/W1861492603","https://openalex.org/W2344474200","https://openalex.org/W2580726517","https://openalex.org/W2604698059","https://openalex.org/W3201312429","https://openalex.org/W4313134354","https://openalex.org/W4313176116","https://openalex.org/W4319301291","https://openalex.org/W4321377343","https://openalex.org/W4390874575","https://openalex.org/W4402727436","https://openalex.org/W4402727865","https://openalex.org/W4402754209","https://openalex.org/W4402915911"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"6D":[1,27,101],"pose":[2,28,52,102],"estimation":[3],"depends":[4],"on":[5],"high-quality":[6,100],"annotated":[7],"datasets,":[8],"yet":[9],"existing":[10],"data":[11],"collection":[12],"pipelines":[13],"remain":[14],"slow,":[15],"hardware-dependent,":[16],"and":[17,35,46,65,95],"labor-intensive.":[18],"We":[19],"propose":[20],"an":[21],"automated,":[22],"modular":[23],"framework":[24],"for":[25,98],"constructing":[26],"datasets":[29],"from":[30],"both":[31],"real":[32],"RGB-D":[33],"capture":[34],"procedural":[36],"simulation.":[37],"The":[38,57],"real-data":[39],"branch":[40,59],"combines":[41],"SAM-based":[42],"initialization,":[43],"video-mask":[44],"propagation,":[45],"FoundationPose":[47],"to":[48,68],"produce":[49],"temporally":[50],"consistent":[51],"labels":[53],"without":[54],"manual":[55],"intervention.":[56],"synthetic":[58],"uses":[60],"BlenderProc":[61],"with":[62],"physics":[63],"simulation":[64],"domain":[66],"randomization":[67],"generate":[69],"diverse,":[70],"photorealistic":[71],"multi-view":[72],"scenes.":[73],"Experiments":[74],"show":[75],"that":[76],"our":[77],"method":[78],"achieves":[79],"human-level":[80],"annotation":[81],"accuracy":[82],"while":[83],"improving":[84],"efficiency":[85],"by":[86],"over":[87],"15":[88],"\u00d7.":[89],"This":[90],"pipeline":[91],"offers":[92],"a":[93],"scalable":[94],"cost-effective":[96],"solution":[97],"building":[99],"datasets.":[103]},"counts_by_year":[],"updated_date":"2026-02-15T06:02:07.359773","created_date":"2026-02-15T00:00:00"}