{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T06:43:00Z","timestamp":1730270580249,"version":"3.28.0"},"reference-count":61,"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"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,10,24]]},"DOI":"10.1109\/iros45743.2020.9341750","type":"proceedings-article","created":{"date-parts":[[2021,2,13]],"date-time":"2021-02-13T02:26:48Z","timestamp":1613183208000},"page":"8073-8080","source":"Crossref","is-referenced-by-count":2,"title":["Learning visual policies for building 3D shape categories"],"prefix":"10.1109","author":[{"given":"Alexander","family":"Pashevich","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Igor","family":"Kalevatykh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ivan","family":"Laptev","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cordelia","family":"Schmid","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","article-title":"Stacked hourglass networks for human pose estimation","author":"newell","year":"2016","journal-title":"ECCV"},{"key":"ref38","article-title":"Time reversal as self-supervision","author":"nair","year":"2020","journal-title":"ICRA"},{"key":"ref33","article-title":"End-to-end training of deep visuomotor policies","author":"levine","year":"2015","journal-title":"JMLR"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511546877"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2013.6707053"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1177\/0278364913495721"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8463162"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2017.XIII.058"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2014.6943079"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2019.XV.004"},{"key":"ref61","article-title":"Deep imitation learning for complex manipulation tasks from virtual reality teleoperation","author":"zhang","year":"2017","journal-title":"ICRA"},{"key":"ref28","article-title":"Reinforcement learning with unsupervised auxiliary tasks","author":"jaderberg","year":"2016","journal-title":"ArXiv"},{"article-title":"Deep reinforcement learning doesn’t work yet","year":"2018","author":"irpan","key":"ref27"},{"key":"ref29","article-title":"Reasoning about physical interactions with object-oriented prediction and planning","author":"janner","year":"2019","journal-title":"ICLRE"},{"key":"ref2","article-title":"Learning to poke by poking: Experiential learning of intuitive physics","author":"agrawal","year":"2016","journal-title":"NIPS"},{"journal-title":"Project webpage","year":"0","key":"ref1"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00319"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2015.7139022"},{"key":"ref21","article-title":"Deep reinforcement learning for robotic manipulation","author":"gu","year":"2016","journal-title":"ICML"},{"key":"ref24","article-title":"Playing atari games with deep reinforcement learning and human checkpoint replay","author":"hosu","year":"2016","journal-title":"ECAI Workshop on Evaluating General Purpose AI"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref26","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"ioffe","year":"2015","journal-title":"ICML"},{"key":"ref25","article-title":"Neural task graphs: Generalizing to unseen tasks from a single video demonstration","author":"huang","year":"2018","journal-title":"CVPR"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2017.XIII.034"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2014.6906922"},{"key":"ref59","article-title":"Form2Fit: Learning Shape Priors for Generalizable Assembly from Disassembly","author":"zakka","year":"2019","journal-title":"ArXiv"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.511"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2019.XV.074"},{"key":"ref56","article-title":"Logic-geometric programming: An optimization-based approach to combined task and motion planning","author":"toussaint","year":"2015","journal-title":"IJAC"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2017.8202133"},{"key":"ref54","article-title":"Intrinsic motivation and automatic curricula via asymmetric self-play","author":"sukhbaatar","year":"2017","journal-title":"ICLRE"},{"key":"ref53","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1109\/MRA.2012.2205651","article-title":"The Open Motion Planning Library","volume":"19","author":"s\u00b8ucan","year":"2012","journal-title":"Robotics & Automation Magazine"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1126\/scirobotics.aat6385"},{"key":"ref10","article-title":"One-shot imitation learning","author":"duan","year":"2017","journal-title":"NIPS"},{"article-title":"Visual Foresight: Model-Based Deep Reinforcement Learning for Vision-Based Robotic Control","year":"2018","author":"ebert","key":"ref11"},{"key":"ref40","article-title":"Modulated policy hierarchies","author":"pashevich","year":"2018","journal-title":"NIPS Deep RL Workshop"},{"article-title":"PDDL2.2: The Language for the Classical Part of IPC-4","year":"2004","author":"edelkamp","key":"ref12"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/70.143350"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(71)90010-5"},{"key":"ref15","article-title":"Reverse curriculum generation for reinforcement learning","author":"florensa","year":"2017","journal-title":"CoRL"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2017.8206247"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-16595-0_11"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1177\/0278364917739114"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1177\/0278364918802962"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2008.10.024"},{"key":"ref3","article-title":"Hindsight experience replay","author":"andrychowicz","year":"2017","journal-title":"NIPS"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8460487"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00185"},{"article-title":"PyBullet, Python module for physics simulation, robotics and machine learning","year":"2016","author":"courmans","key":"ref8"},{"key":"ref7","article-title":"Efficient selectivity and backup operators in monte-carlo tree search","author":"coulom","year":"2006","journal-title":"Computers and Games"},{"key":"ref49","article-title":"Learning by playing - Solving sparse reward tasks from scratch","author":"riedmiller","year":"2018","journal-title":"MLR"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1177\/0278364918761570"},{"key":"ref46","article-title":"Data-efficient deep reinforcement learning for dexterous manipulation","author":"popov","year":"2017","journal-title":"ArXiv"},{"key":"ref45","article-title":"Alvinn: An autonomous land vehicle in a neural network","author":"pomerleau","year":"1989","journal-title":"NIPS"},{"key":"ref48","article-title":"Faster R-CNN: Towards Real-time Object Detection with Region Proposal Networks","author":"ren","year":"2015","journal-title":"NIPS"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8461076"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/IROS40897.2019.8967622"},{"key":"ref41","article-title":"Learning visual policies for building 3d shape categories","author":"pashevich","year":"2020","journal-title":"ArXiv"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2016.7487517"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8793736"}],"event":{"name":"2020 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)","start":{"date-parts":[[2020,10,24]]},"location":"Las Vegas, NV, USA","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\/09341750.pdf?arnumber=9341750","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,28]],"date-time":"2022-06-28T21:52:04Z","timestamp":1656453124000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9341750\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,24]]},"references-count":61,"URL":"https:\/\/doi.org\/10.1109\/iros45743.2020.9341750","relation":{},"subject":[],"published":{"date-parts":[[2020,10,24]]}}}