{"id":"https://openalex.org/W2903167365","doi":"https://doi.org/10.1145/3283289.3283326","title":"Automatic dataset generation for object pose estimation","display_name":"Automatic dataset generation for object pose estimation","publication_year":2018,"publication_date":"2018-11-30","ids":{"openalex":"https://openalex.org/W2903167365","doi":"https://doi.org/10.1145/3283289.3283326","mag":"2903167365"},"language":"en","primary_location":{"id":"doi:10.1145/3283289.3283326","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3283289.3283326","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIGGRAPH Asia 2018 Posters","raw_type":"proceedings-article"},"type":"conference-paper","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/A5050562648","display_name":"Kalenga-Bimpambu Tshilombo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kalenga-Bimpambu Tshilombo","raw_affiliation_strings":["CNRS-AIST"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CNRS-AIST","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023347873","display_name":"Yusuke Yoshiyasu","orcid":"https://orcid.org/0000-0002-0433-9832"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yusuke Yoshiyasu","raw_affiliation_strings":["CNRS-AIST"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CNRS-AIST","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072801488","display_name":"Antonio Gabas","orcid":"https://orcid.org/0000-0001-5598-7699"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Antonio Gabas","raw_affiliation_strings":["CNRS-AIST"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CNRS-AIST","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015836342","display_name":"Kota Suzui","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kota Suzui","raw_affiliation_strings":["CNRS-AIST"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CNRS-AIST","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9994999766349792,"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":0.9994999766349792,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.9994000196456909,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9986000061035156,"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":0.8879663944244385},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8519796133041382},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8120414018630981},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7689282894134521},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7026047706604004},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6671061515808105},{"id":"https://openalex.org/keywords/3d-pose-estimation","display_name":"3D pose estimation","score":0.6481627821922302},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5092259645462036},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4939485192298889},{"id":"https://openalex.org/keywords/articulated-body-pose-estimation","display_name":"Articulated body pose estimation","score":0.44329726696014404},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.43289270997047424},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42358842492103577},{"id":"https://openalex.org/keywords/augmented-reality","display_name":"Augmented reality","score":0.4153362512588501},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3337981700897217},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07352635264396667}],"concepts":[{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.8879663944244385},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8519796133041382},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8120414018630981},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7689282894134521},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7026047706604004},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6671061515808105},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.6481627821922302},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5092259645462036},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4939485192298889},{"id":"https://openalex.org/C22100474","wikidata":"https://www.wikidata.org/wiki/Q4800952","display_name":"Articulated body pose estimation","level":4,"score":0.44329726696014404},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.43289270997047424},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42358842492103577},{"id":"https://openalex.org/C153715457","wikidata":"https://www.wikidata.org/wiki/Q254183","display_name":"Augmented reality","level":2,"score":0.4153362512588501},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3337981700897217},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07352635264396667},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3283289.3283326","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3283289.3283326","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIGGRAPH Asia 2018 Posters","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5936539190","display_name":"Deep learning for action","funder_award_id":"17K18420","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1591870335","https://openalex.org/W2102605133","https://openalex.org/W2163605009","https://openalex.org/W2208045473","https://openalex.org/W2562043770","https://openalex.org/W2796347433","https://openalex.org/W2952606116","https://openalex.org/W2964249569","https://openalex.org/W4212774754"],"related_works":["https://openalex.org/W2946083937","https://openalex.org/W2798721181","https://openalex.org/W4386075737","https://openalex.org/W2951583186","https://openalex.org/W4299867837","https://openalex.org/W2088028039","https://openalex.org/W4382141741","https://openalex.org/W3165753266","https://openalex.org/W1968783203","https://openalex.org/W4206633503"],"abstract_inverted_index":{"Object":[0],"pose":[1,58],"estimation":[2],"based":[3],"on":[4],"a":[5,34,38,51],"RGB":[6],"image":[7],"is":[8],"essential":[9],"in":[10],"accomplishing":[11],"many":[12],"computer":[13],"vision":[14,22],"tasks,":[15],"such":[16],"as":[17],"augmented":[18],"reality":[19],"and":[20,29],"robot":[21],"for":[23,56],"grasping.":[24],"Using":[25],"structure":[26],"from":[27,37],"motion":[28],"domain":[30],"randomization,":[31],"we":[32],"propose":[33],"method":[35],"that,":[36],"set":[39],"of":[40],"images,":[41],"allows":[42],"us":[43],"to":[44,49],"quickly":[45],"generate":[46],"large":[47],"datasets":[48],"train":[50],"Convolutional":[52],"Neural":[53],"Network":[54],"(ConvNet)":[55],"object":[57],"estimation.":[59]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
