{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T07:26:10Z","timestamp":1790753170778,"version":"4.1.0"},"reference-count":33,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,5]]},"DOI":"10.1109\/icra.2017.7989023","type":"proceedings-article","created":{"date-parts":[[2017,7,25]],"date-time":"2017-07-25T21:44:28Z","timestamp":1501019068000},"page":"173-180","source":"Crossref","is-referenced-by-count":141,"title":["SE3-nets: Learning rigid body motion using deep neural networks"],"prefix":"10.1109","author":[{"given":"Arunkumar","family":"Byravan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dieter","family":"Fox","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298631"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2014.X.030"},{"key":"ref31","author":"agrawal","year":"2016","journal-title":"Learning to poke by poking Experiential learning of intuitive physics"},{"key":"ref30","author":"ioffe","year":"2015","journal-title":"Batch Normalization Accelerating Deep Network Training by Reducing Internal Covariate Shift"},{"key":"ref10","first-page":"1","article-title":"Learning modular and transferable forward models of the motions of push manipulated objects","author":"kopicki","year":"2016","journal-title":"Autonomous Robots"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2014.6907443"},{"key":"ref12","author":"bohg","year":"2016","journal-title":"Interactive perception Leveraging action in perception and perception in action"},{"key":"ref13","first-page":"2728","article-title":"Embed to control: A locally linear latent dynamics model for control from raw images","author":"watter","year":"2015","journal-title":"NIPS"},{"key":"ref14","author":"wahlstrom","year":"2015","journal-title":"From pixels to torques Policy learning with deep dynamical models"},{"key":"ref15","author":"lerer","year":"2016","journal-title":"Learning physical intuition of block towers by example"},{"key":"ref16","author":"fragkiadaki","year":"2015","journal-title":"Learning visual predictive models of physics for playing billiards"},{"key":"ref17","first-page":"3521","article-title":"Newtonian scene understanding: Unfolding the dynamics of objects in static images","author":"mottaghi","year":"2016","journal-title":"CVPR"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.13"},{"key":"ref19","article-title":"Unsupervised learning for physical interaction through video prediction","author":"finn","year":"2016","journal-title":"NIPS"},{"key":"ref28","article-title":"Torch7: A matlab-like environment for machine learning","author":"collobert","year":"2011","journal-title":"BigLearn NIPS Workshop"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1306572110"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33885-4_60"},{"key":"ref3","article-title":"A convex polynomial force-motion model for planar sliding: Identification and application","author":"zhou","year":"2016","journal-title":"IEEE"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1111\/j.0963-7214.2004.00281.x"},{"key":"ref29","author":"kingma","year":"2014","journal-title":"Adam A method for stochastic optimization"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1037\/a0031912"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553508"},{"key":"ref7","author":"whitney","year":"2016","journal-title":"Disentangled representations in neural models"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-06698-1_42"},{"key":"ref9","first-page":"465","article-title":"Pilco: A model-based and data-efficient approach to policy search","author":"deisenroth","year":"2011","journal-title":"ICML"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2012.6386109"},{"key":"ref20","first-page":"2530","article-title":"Deep convolutional inverse graphics network","author":"kulkarni","year":"2015","journal-title":"NIPS"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-49409-8_9"},{"key":"ref21","first-page":"1099","article-title":"Weakly-supervised disentangling with recurrent transformations for 3d view synthesis","author":"yang","year":"2015","journal-title":"NIPS"},{"key":"ref24","author":"ba","year":"2014","journal-title":"Multiple object recognition with visual attention"},{"key":"ref23","author":"gregor","year":"2015","journal-title":"Draw A recurrent neural network for image generation"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref25","first-page":"2008","article-title":"Spatial transformer networks","author":"jaderberg","year":"2015","journal-title":"NIPS"}],"event":{"name":"2017 IEEE International Conference on Robotics and Automation (ICRA)","location":"Singapore, Singapore","start":{"date-parts":[[2017,5,29]]},"end":{"date-parts":[[2017,6,3]]}},"container-title":["2017 IEEE International Conference on Robotics and Automation (ICRA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7960754\/7988677\/07989023.pdf?arnumber=7989023","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,8,16]],"date-time":"2017-08-16T16:18:48Z","timestamp":1502900328000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/7989023\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,5]]},"references-count":33,"URL":"https:\/\/doi.org\/10.1109\/icra.2017.7989023","relation":{},"subject":[],"published":{"date-parts":[[2017,5]]}}}