{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T08:13:46Z","timestamp":1769588026986,"version":"3.49.0"},"reference-count":42,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,10,24]],"date-time":"2020-10-24T00:00:00Z","timestamp":1603497600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,10,24]],"date-time":"2020-10-24T00:00:00Z","timestamp":1603497600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,10,24]],"date-time":"2020-10-24T00:00:00Z","timestamp":1603497600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100006831","name":"United States Air Force","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006831","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,10,24]]},"DOI":"10.1109\/iros45743.2020.9340860","type":"proceedings-article","created":{"date-parts":[[2021,3,15]],"date-time":"2021-03-15T14:49:56Z","timestamp":1615819796000},"page":"10580-10587","source":"Crossref","is-referenced-by-count":15,"title":["Learning Orientation Distributions for Object Pose Estimation"],"prefix":"10.1109","author":[{"given":"Brian","family":"Okorn","sequence":"first","affiliation":[]},{"given":"Mengyun","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Martial","family":"Hebert","sequence":"additional","affiliation":[]},{"given":"David","family":"Held","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/s00006-016-0683-9"},{"key":"ref38","volume":"2","author":"dam","year":"1998","journal-title":"Quaternions Interpolation and Animation"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1176342874"},{"key":"ref32","article-title":"Unscented orientation estimation based on the bingham distribution","author":"gilitschenski","year":"2015","journal-title":"IEEE Transactions on Automatic Control"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2017.XIII.016"},{"key":"ref30","article-title":"What uncertainties do we need in bayesian deep learning for computer vision?","author":"kendall","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.4018\/978-1-4666-2672-0.ch002"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1177\/0278364909352700"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/B978-0-08-050755-2.50036-1"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/INDIN.2017.8104794"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.169"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.258"},{"key":"ref11","article-title":"Deep object pose estimation for semantic robotic grasping of household objects","author":"tremblay","year":"2018"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2017.8206470"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2017.7989165"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/358669.358692"},{"key":"ref15","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":"ref16","article-title":"Real-time scalable 6dof pose estimation for textureless objects","author":"cao","year":"2016","journal-title":"ICRA"},{"key":"ref17","article-title":"Detection and fine 3d pose estimation of texture-less objects in rgb-d images","author":"hoda?","year":"2015","journal-title":"IROS"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2010.5540108"},{"key":"ref19","article-title":"Implicit 3d orientation learning for 6d object detection from rgb images","author":"sundermeyer","year":"2018","journal-title":"ECCV"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00694"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ROBOT.2009.5152709"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2019.XV.049"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8460696"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1177\/0278364913488805"},{"key":"ref29","article-title":"Dropout as a bayesian approximation: Representing model uncertainty in deep learning","author":"gal","year":"2016","journal-title":"ICML"},{"key":"ref5","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-642-28572-1_17","article-title":"Towards reliable grasping and manipulation in household environments","author":"ciocarlie","year":"2014","journal-title":"Experimental Robotics"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00346"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2018.XIV.019"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2016.XII.002"},{"key":"ref9","article-title":"Learning 6d object pose estimation using 3d object coordinates","author":"brachmann","year":"2014","journal-title":"ECCV"},{"key":"ref1","article-title":"Planning for grasp selection of partially occluded objects","author":"kim","year":"2016","journal-title":"ICRA"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298930"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.308"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.416"},{"key":"ref42","article-title":"Bayesian segnet: Model uncertainty in deep convolutional encoder-decoder architectures for scene understanding","author":"kendall","year":"2015"},{"key":"ref24","article-title":"Monte carlo pose estimation with quaternion kernels and the bingham distribution","author":"glover","year":"2012","journal-title":"RSS"},{"key":"ref41","article-title":"Critical hyper-parameters: No random, no cry","author":"bousquet","year":"2017"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/s10514-017-9633-1"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.366"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/AQTR.2016.7501381"}],"event":{"name":"2020 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)","location":"Las Vegas, NV, USA","start":{"date-parts":[[2020,10,24]]},"end":{"date-parts":[[2021,1,24]]}},"container-title":["2020 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9340668\/9340635\/09340860.pdf?arnumber=9340860","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,28]],"date-time":"2022-06-28T21:57:00Z","timestamp":1656453420000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9340860\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,24]]},"references-count":42,"URL":"https:\/\/doi.org\/10.1109\/iros45743.2020.9340860","relation":{},"subject":[],"published":{"date-parts":[[2020,10,24]]}}}