GPLAC: Generalizing Vision-Based Robotic Skills Using Weakly Labeled Images
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Sergey Levine | Avi Singh | Larry Yang | S. Levine | Avi Singh | Larry Yang
[1] Max Welling,et al. Auto-Encoding Variational Bayes , 2013, ICLR.
[2] Dean Pomerleau,et al. ALVINN, an autonomous land vehicle in a neural network , 2015 .
[3] Zhe Gan,et al. Variational Autoencoder for Deep Learning of Images, Labels and Captions , 2016, NIPS.
[4] Sergey Levine,et al. Deep spatial autoencoders for visuomotor learning , 2015, 2016 IEEE International Conference on Robotics and Automation (ICRA).
[5] R. Held,et al. MOVEMENT-PRODUCED STIMULATION IN THE DEVELOPMENT OF VISUALLY GUIDED BEHAVIOR. , 1963, Journal of comparative and physiological psychology.
[6] Ole Winther,et al. Auxiliary Deep Generative Models , 2016, ICML.
[7] Max Welling,et al. Semi-supervised Learning with Deep Generative Models , 2014, NIPS.
[8] Mathieu Aubry,et al. Dex-Net 1.0: A cloud-based network of 3D objects for robust grasp planning using a Multi-Armed Bandit model with correlated rewards , 2016, 2016 IEEE International Conference on Robotics and Automation (ICRA).
[9] Kate Saenko,et al. Return of Frustratingly Easy Domain Adaptation , 2015, AAAI.
[10] Martin A. Riedmiller,et al. Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images , 2015, NIPS.
[11] Jürgen Schmidhuber,et al. Evolving large-scale neural networks for vision-based reinforcement learning , 2013, GECCO '13.
[12] Abhinav Gupta,et al. Supersizing self-supervision: Learning to grasp from 50K tries and 700 robot hours , 2015, 2016 IEEE International Conference on Robotics and Automation (ICRA).
[13] Michael I. Jordan,et al. Learning Transferable Features with Deep Adaptation Networks , 2015, ICML.
[14] Sergey Levine,et al. End-to-End Training of Deep Visuomotor Policies , 2015, J. Mach. Learn. Res..
[15] Xin Zhang,et al. End to End Learning for Self-Driving Cars , 2016, ArXiv.
[16] J. Peters,et al. Using Reward-weighted Regression for Reinforcement Learning of Task Space Control , 2007, 2007 IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning.
[17] Sergey Levine,et al. Trust Region Policy Optimization , 2015, ICML.
[18] Alex Graves,et al. DRAW: A Recurrent Neural Network For Image Generation , 2015, ICML.
[19] Xiaoou Tang,et al. Facial Landmark Detection by Deep Multi-task Learning , 2014, ECCV.
[20] Yuval Tassa,et al. MuJoCo: A physics engine for model-based control , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[21] Razvan Pascanu,et al. Sim-to-Real Robot Learning from Pixels with Progressive Nets , 2016, CoRL.
[22] François Laviolette,et al. Domain-Adversarial Neural Networks , 2014, ArXiv.
[23] S. Shankar Sastry,et al. A mathematical introduction to robotics manipulation , 1994 .
[24] Dumitru Erhan,et al. Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[25] Nikos Komodakis,et al. Object Detection via a Multi-region and Semantic Segmentation-Aware CNN Model , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[26] Akansel Cosgun,et al. Push planning for object placement on cluttered table surfaces , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[27] Jitendra Malik,et al. Learning to Poke by Poking: Experiential Learning of Intuitive Physics , 2016, NIPS.
[28] Tapani Raiko,et al. Semi-supervised Learning with Ladder Networks , 2015, NIPS.
[29] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[30] Yann LeCun,et al. Learning to Linearize Under Uncertainty , 2015, NIPS.
[31] Danica Kragic,et al. Deep predictive policy training using reinforcement learning , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[32] Jeannette Bohg,et al. Leveraging big data for grasp planning , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).
[33] George Trigeorgis,et al. Domain Separation Networks , 2016, NIPS.
[34] Ivan Laptev,et al. Is object localization for free? - Weakly-supervised learning with convolutional neural networks , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[35] Ming-Yu Liu,et al. Coupled Generative Adversarial Networks , 2016, NIPS.
[36] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[37] Kibok Lee,et al. Augmenting Supervised Neural Networks with Unsupervised Objectives for Large-scale Image Classification , 2016, ICML.
[38] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[39] Yoshua Bengio,et al. Show, Attend and Tell: Neural Image Caption Generation with Visual Attention , 2015, ICML.
[40] Yuval Tassa,et al. Continuous control with deep reinforcement learning , 2015, ICLR.
[41] Kate Saenko,et al. High precision grasp pose detection in dense clutter , 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[42] Victor S. Lempitsky,et al. Unsupervised Domain Adaptation by Backpropagation , 2014, ICML.
[43] Siddhartha S. Srinivasa,et al. A Planning Framework for Non-Prehensile Manipulation under Clutter and Uncertainty , 2012, Autonomous Robots.
[44] Trevor Darrell,et al. Deep Domain Confusion: Maximizing for Domain Invariance , 2014, CVPR 2014.
[45] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[46] Luca Maria Gambardella,et al. Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence Flexible, High Performance Convolutional Neural Networks for Image Classification , 2022 .
[47] Jitendra Malik,et al. Simultaneous Detection and Segmentation , 2014, ECCV.
[48] Yann LeCun,et al. Stacked What-Where Auto-encoders , 2015, ArXiv.
[49] Jitendra Malik,et al. R-CNNs for Pose Estimation and Action Detection , 2014, ArXiv.
[50] Oussama Khatib,et al. A unified approach for motion and force control of robot manipulators: The operational space formulation , 1987, IEEE J. Robotics Autom..
[51] James Davidson,et al. Supervision via competition: Robot adversaries for learning tasks , 2016, 2017 IEEE International Conference on Robotics and Automation (ICRA).
[52] Wojciech Zaremba,et al. Improved Techniques for Training GANs , 2016, NIPS.
[53] Abhinav Gupta,et al. Designing deep networks for surface normal estimation , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[54] Michael Gasser,et al. The Development of Embodied Cognition: Six Lessons from Babies , 2005, Artificial Life.
[55] Alexander J. Smola,et al. Stacked Attention Networks for Image Question Answering , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[56] Abhinav Gupta,et al. Learning to push by grasping: Using multiple tasks for effective learning , 2016, 2017 IEEE International Conference on Robotics and Automation (ICRA).
[57] Richard M. Murray,et al. A Mathematical Introduction to Robotic Manipulation , 1994 .
[58] Sergey Levine,et al. Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection , 2016, Int. J. Robotics Res..