{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T17:29:56Z","timestamp":1779384596603,"version":"3.53.1"},"reference-count":36,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,5,30]],"date-time":"2021-05-30T00:00:00Z","timestamp":1622332800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,5,30]],"date-time":"2021-05-30T00:00:00Z","timestamp":1622332800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,5,30]],"date-time":"2021-05-30T00:00:00Z","timestamp":1622332800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,5,30]]},"DOI":"10.1109\/icra48506.2021.9561475","type":"proceedings-article","created":{"date-parts":[[2021,10,20]],"date-time":"2021-10-20T00:28:35Z","timestamp":1634689715000},"page":"11081-11087","source":"Crossref","is-referenced-by-count":43,"title":["CloudAAE: Learning 6D Object Pose Regression with On-line Data Synthesis on Point Clouds"],"prefix":"10.1109","author":[{"given":"Ge","family":"Gao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mikko","family":"Lauri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaolin","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianwei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Simone","family":"Frintrop","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/MRA.2015.2448951"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP40778.2020.9191119"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00469"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.169"},{"key":"ref36","article-title":"BlenderProc","author":"denninger","year":"2019"},{"key":"ref35","first-page":"2579","article-title":"Visualizing data using t-sne","volume":"9","author":"van der maaten","year":"2008","journal-title":"Journal of Machine Learning Research"},{"key":"ref34","article-title":"Open3D: A modern library for 3D data processing","author":"zhou","year":"2018"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00102"},{"key":"ref11","article-title":"PointNet: Deep learning on point sets for 3D classification and segmentation","author":"qi","year":"2017","journal-title":"CVPR"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00346"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01165"},{"key":"ref14","article-title":"Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion","volume":"11","author":"vincent","year":"2010","journal-title":"Journal of Machine Learning Research"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2020.3005121"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00203"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00038"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.413"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00776"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2644615"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2018.XIV.019"},{"key":"ref27","article-title":"Occlusion resistant object rotation regression from point cloud segments","author":"gao","year":"2018","journal-title":"ECCV Workshop on Recovering 6D Object Pose"},{"key":"ref3","article-title":"LabelFusion: A pipeline for generating ground truth labels for real RGBD data of cluttered scenes","author":"marion","year":"2018","journal-title":"ICRA"},{"key":"ref6","article-title":"Implicit 3D orientation learning for 6D object detection from RGB images","author":"sundermeyer","year":"2018","journal-title":"ECCV"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10605-2_35"},{"key":"ref5","article-title":"BOP: Benchmark for 6D object pose estimation","author":"hoda?","year":"2018","journal-title":"ECCV"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA40945.2020.9197461"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2017.7989663"},{"key":"ref2","article-title":"BOP challenge 2020 on 6D object localization","author":"hoda?","year":"2020","journal-title":"ECCV Workshop on Recovering 6D Object Pose"},{"key":"ref9","article-title":"Model based training, detection and pose estimation of texture-less 3D objects in heavily cluttered scenes","author":"hinterstoisser","year":"2012","journal-title":"ACCV"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2017.7989165"},{"key":"ref20","article-title":"Deep object pose estimation for semantic robotic grasping of household objects","author":"tremblay","year":"2018","journal-title":"CoRL"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2017.8202206"},{"key":"ref21","article-title":"Photorealistic image synthesis for object instance detection","author":"hoda?","year":"2019","journal-title":"ICIP"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00217"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.308"},{"key":"ref26","doi-asserted-by":"crossref","DOI":"10.1145\/3326362","article-title":"Dynamic graph CNN for learning on point clouds","author":"wang","year":"2019","journal-title":"ACM Transactions on Graphics (TOG)"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/1276377.1276407"}],"event":{"name":"2021 IEEE International Conference on Robotics and Automation (ICRA)","location":"Xi'an, China","start":{"date-parts":[[2021,5,30]]},"end":{"date-parts":[[2021,6,5]]}},"container-title":["2021 IEEE International Conference on Robotics and Automation (ICRA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9560720\/9560666\/09561475.pdf?arnumber=9561475","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T15:47:15Z","timestamp":1652197635000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9561475\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,30]]},"references-count":36,"URL":"https:\/\/doi.org\/10.1109\/icra48506.2021.9561475","relation":{},"subject":[],"published":{"date-parts":[[2021,5,30]]}}}