COS598F Bibliography

Generative Adversarial Networks

[shrivastava2016learning] Shrivastava, Ashish, Pfister, Tomas, Tuzel, Oncel, Susskind, Josh, Wang, Wenda, Webb, Russ,
"Learning from Simulated and Unsupervised Images through Adversarial Training,"
arXiv preprint arXiv:1612.07828, 2016.
paper arXiv code summary google scholar
 
[goodfellow2016nips] Goodfellow, Ian,
"NIPS 2016 Tutorial: Generative Adversarial Networks,"
arXiv preprint arXiv:1701.00160, 2016.
paper arXiv slides abstract summary google scholar
 
[isola2016image] Isola, Phillip, Zhu, Jun-Yan, Zhou, Tinghui, Efros, Alexei A,
"Image-to-image translation with conditional adversarial networks,"
arXiv preprint arXiv:1611.07004, 2016.
paper arXiv project code abstract summary google scholar
 
[chen2016infogan] Chen, Xi, Duan, Yan, Houthooft, Rein, Schulman, John, Sutskever, Ilya, Abbeel, Pieter,
"InfoGAN: Interpretable representation learning by information maximizing generative adversarial nets,"
Advances in Neural Information Processing Systems, 2016, pp. 2172-2180.
paper arXiv code summary google scholar
 
[van2016conditional] van den Oord, Aaron, Kalchbrenner, Nal, Espeholt, Lasse, Vinyals, Oriol, Graves, Alex, others,
"Conditional image generation with PixelCNN decoders,"
Advances in Neural Information Processing Systems, 2016, pp. 4790-4798.
paper arXiv code abstract summary google scholar
 
[salimans2016improved] Salimans, Tim, Goodfellow, Ian, Zaremba, Wojciech, Cheung, Vicki, Radford, Alec, Chen, Xi,
"Improved techniques for training GANs,"
Advances in Neural Information Processing Systems, 2016, pp. 2226-2234.
paper arXiv code abstract summary google scholar
 
[radford2015unsupervised] Radford, Alec, Metz, Luke, Chintala, Soumith,
"Unsupervised representation learning with deep convolutional generative adversarial networks,"
arXiv preprint arXiv:1511.06434, 2015.
paper arXiv code abstract summary google scholar
 
[goodfellow2014generative] Goodfellow, Ian, Pouget-Abadie, Jean, Mirza, Mehdi, Xu, Bing, Warde-Farley, David, Ozair, Sherjil, Courville, Aaron, Bengio, Yoshua,
"Generative adversarial nets,"
Advances in neural information processing systems, 2014, pp. 2672-2680.
paper arXiv abstract summary google scholar
 
[mirza2014conditional] Mirza, Mehdi, Osindero, Simon,
"Conditional generative adversarial nets,"
arXiv preprint arXiv:1411.1784, 2014.
google scholar
 
[reed2016generative] Reed, Scott, Akata, Zeynep, Yan, Xinchen, Logeswaran, Lajanugen, Schiele, Bernt, Lee, Honglak,
"Generative adversarial text to image synthesis,"
Proceedings of The 33rd International Conference on Machine Learning, 3, 2016.
google scholar
 
[odena2016conditional] Odena, Augustus, Olah, Christopher, Shlens, Jonathon,
"Conditional image synthesis with auxiliary classifier gans,"
arXiv preprint arXiv:1610.09585, 2016.
google scholar
 
[zhao2016energy] Zhao, Junbo, Mathieu, Michael, LeCun, Yann,
"Energy-based generative adversarial network,"
arXiv preprint arXiv:1609.03126, 2016.
google scholar
 
[dai2017towards] Dai, Bo, Lin, Dahua, Urtasun, Raquel, Fidler, Sanja,
"Towards Diverse and Natural Image Descriptions via a Conditional GAN,"
arXiv preprint arXiv:1703.06029, 2017.
google scholar
 
[arjovsky2017wasserstein] Arjovsky, Martin, Chintala, Soumith, Bottou, L\'eon,
"Wasserstein gan,"
arXiv preprint arXiv:1701.07875, 2017.
google scholar
 


Learned Representations of 3D Shape

[wu2016learning] Wu, Jiajun, Zhang, Chengkai, Xue, Tianfan, Freeman, Bill, Tenenbaum, Josh,
"Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling,"
Advances in Neural Information Processing Systems, 2016, pp. 82-90.
paper video arXiv project code abstract google scholar

 
[brock2016generative] Brock, Andrew, Lim, Theodore, Ritchie, JM, Weston, Nick,
"Generative and Discriminative Voxel Modeling with Convolutional Neural Networks,"
arXiv preprint arXiv:1608.04236, 2016.
paper arXiv code abstract google scholar
 
[rezende2016unsupervised] Rezende, Danilo Jimenez, Eslami, SM Ali, Mohamed, Shakir, Battaglia, Peter, Jaderberg, Max, Heess, Nicolas,
"Unsupervised learning of 3D structure from images,"
Advances In Neural Information Processing Systems, 2016, pp. 4997-5005.
paper video arXiv supplemental abstract summary google scholar

 
[sharma2016vconv] Sharma, Abhishek, Grau, Oliver, Fritz, Mario,
"Vconv-dae: Deep volumetric shape learning without object labels,"
Computer Vision-ECCV 2016 Workshops, 2016, pp. 236-250.
arXiv project google scholar

 
[girdhar2016learning] Girdhar, Rohit, Fouhey, David F, Rodriguez, Mikel, Gupta, Abhinav,
"Learning a predictable and generative vector representation for objects,"
European Conference on Computer Vision, 2016, pp. 484-499.
paper arXiv code abstract google scholar

 


Self-Supervised Learning

[pathak2016context] Pathak, Deepak, Krahenbuhl, Philipp, Donahue, Jeff, Darrell, Trevor, Efros, Alexei A,
"Context encoders: Feature learning by inpainting,"
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 2536-2544.
paper project code google scholar
 
[agrawal2015learning] Agrawal, Pulkit, Carreira, Joao, Malik, Jitendra,
"Learning to see by moving,"
Proceedings of the IEEE International Conference on Computer Vision, 2015, pp. 37-45.
paper project code google scholar
 
[zamir2016generic] Zamir, Amir R, Wekel, Tilman, Agrawal, Pulkit, Wei, Colin, Malik, Jitendra, Savarese, Silvio,
"Generic 3d representation via pose estimation and matching,"
European Conference on Computer Vision, 2016, pp. 535-553.
paper project google scholar
 
[zeng20163dmatch] Zeng, Andy, Song, Shuran, Nie\ssner, Matthias, Fisher, Matthew, Xiao, Jianxiong, Funkhouser, Thomas,
"3DMatch: Learning Local Geometric Descriptors from RGB-D Reconstructions,"
arXiv preprint arXiv:1603.08182, 2016.
paper project code google scholar
 
[schmidt2017self] Schmidt, Tanner, Newcombe, Richard, Fox, Dieter,
"Self-Supervised Visual Descriptor Learning for Dense Correspondence,"
IEEE Robotics and Automation Letters, 2, 2, IEEE, 2017, pp. 420-427.
paper google scholar
 
[pinto2016supersizing] Pinto, Lerrel, Gupta, Abhinav,
"Supersizing self-supervision: Learning to grasp from 50k tries and 700 robot hours,"
Robotics and Automation (ICRA), 2016 IEEE International Conference on, 2016, pp. 3406-3413.
paper arXiv google scholar
 
[mottaghi2016happens] Mottaghi, Roozbeh, Rastegari, Mohammad, Gupta, Abhinav, Farhadi, Ali,
"“What happens if...” Learning to Predict the Effect of Forces in Images,"
European Conference on Computer Vision, 2016, pp. 269-285.
paper arXiv google scholar
 
[sofman2006improving] Sofman, Boris, Lin, Ellie, Bagnell, J Andrew, Cole, John, Vandapel, Nicolas, Stentz, Anthony,
"Improving robot navigation through self-supervised online learning,"
Journal of Field Robotics, 23, 11-12, Wiley Online Library, 2006, pp. 1059-1075.
google scholar
 


Learning from RGB-D Panorama

[armeni2017joint] Armeni, Iro, Sax, Sasha, Zamir, Amir R, Savarese, Silvio,
"Joint 2D-3D-Semantic Data for Indoor Scene Understanding,"
arXiv preprint arXiv:1702.01105, 2017.
paper arXiv data google scholar
 
[armeni20163d] Armeni, Iro, Sener, Ozan, Zamir, Amir R, Jiang, Helen, Brilakis, Ioannis, Fischer, Martin, Savarese, Silvio,
"3D semantic parsing of large-scale indoor spaces,"
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 1534-1543.
paper project poster supplemental data abstract google scholar
 


Learning from Video

[karpathy2014large] Karpathy, Andrej, Toderici, George, Shetty, Sanketh, Leung, Thomas, Sukthankar, Rahul, Fei-Fei, Li,
"Large-scale video classification with convolutional neural networks,"
Proceedings of the IEEE conference on Computer Vision and Pattern Recognition, 2014, pp. 1725-1732.
paper google scholar
 
[srivastava2015unsupervised] Srivastava, Nitish, Mansimov, Elman, Salakhutdinov, Ruslan,
"Unsupervised Learning of Video Representations using LSTMs.,"
ICML, 2015, pp. 843-852.
google scholar
 
[wang2015unsupervised] Wang, Xiaolong, Gupta, Abhinav,
"Unsupervised learning of visual representations using videos,"
Proceedings of the IEEE International Conference on Computer Vision, 2015, pp. 2794-2802.
google scholar
 
[yeung2016end] Yeung, Serena, Russakovsky, Olga, Mori, Greg, Fei-Fei, Li,
"End-to-end learning of action detection from frame glimpses in videos,"
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 2678-2687.
paper google scholar
 
[finn2016unsupervised] Finn, Chelsea, Goodfellow, Ian, Levine, Sergey,
"Unsupervised learning for physical interaction through video prediction,"
Advances In Neural Information Processing Systems, 2016, pp. 64-72.
google scholar
 
[donahue2015long] Donahue, Jeffrey, Anne Hendricks, Lisa, Guadarrama, Sergio, Rohrbach, Marcus, Venugopalan, Subhashini, Saenko, Kate, Darrell, Trevor,
"Long-term recurrent convolutional networks for visual recognition and description,"
Proceedings of the IEEE conference on computer vision and pattern recognition, 2015, pp. 2625-2634.
google scholar
 
[huang2017unsupervised] Huang, De-An, Lim, Joseph J, Fei-Fei, Li, Niebles, Juan Carlos,
"Unsupervised Visual-Linguistic Reference Resolution in Instructional Videos,"
arXiv preprint arXiv:1703.02521, 2017.
google scholar
 
[kalchbrenner2016video] Kalchbrenner, Nal, Oord, Aaron van den, Simonyan, Karen, Danihelka, Ivo, Vinyals, Oriol, Graves, Alex, Kavukcuoglu, Koray,
"Video pixel networks,"
arXiv preprint arXiv:1610.00527, 2016.
google scholar
 
[luo2017unsupervised] Luo, Zelun, Peng, Boya, Huang, De-An, Alahi, Alexandre, Fei-Fei, Li,
"Unsupervised Learning of Long-Term Motion Dynamics for Videos,"
arXiv preprint arXiv:1701.01821, 2017.
google scholar
 
[oh2015action] Oh, Junhyuk, Guo, Xiaoxiao, Lee, Honglak, Lewis, Richard L, Singh, Satinder,
"Action-conditional video prediction using deep networks in atari games,"
Advances in Neural Information Processing Systems, 2015, pp. 2863-2871.
google scholar
 
[held2016learning] Held, David, Thrun, Sebastian, Savarese, Silvio,
"Learning to track at 100 fps with deep regression networks,"
European Conference on Computer Vision, 2016, pp. 749-765.
google scholar
 
[simonyan2014two] Simonyan, Karen, Zisserman, Andrew,
"Two-stream convolutional networks for action recognition in videos,"
Advances in neural information processing systems, 2014, pp. 568-576.
google scholar
 
[fischer2015flownet] Fischer, Philipp, Dosovitskiy, Alexey, Ilg, Eddy, H\"ausser, Philip, Haz\irba\cs, Caner, Golkov, Vladimir, van der Smagt, Patrick, Cremers, Daniel, Brox, Thomas,
"Flownet: Learning optical flow with convolutional networks,"
arXiv preprint arXiv:1504.06852, 2015.
google scholar
 
[mathieu2015deep] Mathieu, Michael, Couprie, Camille, LeCun, Yann,
"Deep multi-scale video prediction beyond mean square error,"
arXiv preprint arXiv:1511.05440, 2015.
paper google scholar
 
[vondrick2016anticipating] Vondrick, Carl, Pirsiavash, Hamed, Torralba, Antonio,
"Anticipating visual representations from unlabeled video,"
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 98-106.
google scholar
 
[2017arXiv170307684N] Neverova, N., Luc, P., Couprie, C., Verbeek, J.,,
"Predicting Deeper into the Future of Semantic Segmentation,"
ArXiv e-prints, 2017.
google scholar
 
[DBLP:journals/corr/JiangG16] Hao Jiang,,
"Seeing Invisible Poses: Estimating 3D Body Pose from Egocentric Video,"
CoRR, abs/1603.07763, 2016.
google scholar
 


Deep Reinforcement Learning

[mnih2013playing] Mnih, Volodymyr, Kavukcuoglu, Koray, Silver, David, Graves, Alex, Antonoglou, Ioannis, Wierstra, Daan, Riedmiller, Martin,
"Playing atari with deep reinforcement learning,"
arXiv preprint arXiv:1312.5602, 2013.
paper google scholar
 
[mnih2015human] Mnih, Volodymyr, Kavukcuoglu, Koray, Silver, David, Rusu, Andrei A, Veness, Joel, Bellemare, Marc G, Graves, Alex, Riedmiller, Martin, Fidjeland, Andreas K, Ostrovski, Georg, others,
"Human-level control through deep reinforcement learning,"
Nature, 518, 7540, Nature Research, 2015, pp. 529-533.
paper google scholar
 
[ba2014multiple] Ba, Jimmy, Mnih, Volodymyr, Kavukcuoglu, Koray,
"Multiple object recognition with visual attention,"
arXiv preprint arXiv:1412.7755, 2014.
google scholar
 
[dosovitskiy2016learning] Dosovitskiy, Alexey, Koltun, Vladlen,
"Learning to act by predicting the future,"
International Conference on Learning Representations (ICLR), 2016.
paper video arXiv project google scholar
 
[levine2016end] Levine, Sergey, Finn, Chelsea, Darrell, Trevor, Abbeel, Pieter,
"End-to-end training of deep visuomotor policies,"
Journal of Machine Learning Research, 17, 39, 2016, pp. 1-40.
google scholar
 
[silver2016mastering] Silver, David, Huang, Aja, Maddison, Chris J, Guez, Arthur, Sifre, Laurent, Van Den Driessche, George, Schrittwieser, Julian, Antonoglou, Ioannis, Panneershelvam, Veda, Lanctot, Marc, others,
"Mastering the game of Go with deep neural networks and tree search,"
Nature, 529, 7587, Nature Publishing Group, 2016, pp. 484-489.
google scholar
 
[mnih2016asynchronous] Mnih, Volodymyr, Badia, Adria Puigdomenech, Mirza, Mehdi, Graves, Alex, Lillicrap, Timothy P, Harley, Tim, Silver, David, Kavukcuoglu, Koray,
"Asynchronous methods for deep reinforcement learning,"
International Conference on Machine Learning, 2016.
paper google scholar
 
[shelhamer2016loss] Shelhamer, Evan, Mahmoudieh, Parsa, Argus, Max, Darrell, Trevor,
"Loss is its own Reward: Self-Supervision for Reinforcement Learning,"
arXiv preprint arXiv:1612.07307, 2016.
google scholar
 
[salimans2017evolution] Salimans, Tim, Ho, Jonathan, Chen, Xi, Sutskever, Ilya,
"Evolution Strategies as a Scalable Alternative to Reinforcement Learning,"
arXiv preprint arXiv:1703.03864, 2017.
google scholar
 


Cross-Modal Learning with Text

[mao2016generation] Mao, Junhua, Huang, Jonathan, Toshev, Alexander, Camburu, Oana, Yuille, Alan L, Murphy, Kevin,
"Generation and comprehension of unambiguous object descriptions,"
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 11-20.
paper google scholar
 
[andreas2016learning] Andreas, Jacob, Rohrbach, Marcus, Darrell, Trevor, Klein, Dan,
"Learning to compose neural networks for question answering,"
arXiv preprint arXiv:1601.01705, 2016.
paper google scholar
 
[wang2016learning] Wang, Sida I, Liang, Percy, Manning, Christopher D,
"Learning language games through interaction,"
arXiv preprint arXiv:1606.02447, 2016.
paper google scholar
 
[donahue2015long] Donahue, Jeffrey, Anne Hendricks, Lisa, Guadarrama, Sergio, Rohrbach, Marcus, Venugopalan, Subhashini, Saenko, Kate, Darrell, Trevor,
"Long-term recurrent convolutional networks for visual recognition and description,"
Proceedings of the IEEE conference on computer vision and pattern recognition, 2015, pp. 2625-2634.
google scholar
 
[socher2014grounded] Socher, Richard, Karpathy, Andrej, Le, Quoc V, Manning, Christopher D, Ng, Andrew Y,
"Grounded compositional semantics for finding and describing images with sentences,"
Transactions of the Association for Computational Linguistics, 2, 2014, pp. 207-218.
google scholar
 
[karpathy2015deep] Karpathy, Andrej, Fei-Fei, Li,
"Deep visual-semantic alignments for generating image descriptions,"
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015, pp. 3128-3137.
google scholar
 
[johnson2016densecap] Johnson, Justin, Karpathy, Andrej, Fei-Fei, Li,
"Densecap: Fully convolutional localization networks for dense captioning,"
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 4565-4574.
google scholar
 
[xu2015show] Xu, Kelvin, Ba, Jimmy, Kiros, Ryan, Cho, Kyunghyun, Courville, Aaron C, Salakhutdinov, Ruslan, Zemel, Richard S, Bengio, Yoshua,
"Show, Attend and Tell: Neural Image Caption Generation with Visual Attention.,"
ICML, 14, 2015, pp. 77-81.
google scholar
 
[vinyals2015show] Vinyals, Oriol, Toshev, Alexander, Bengio, Samy, Erhan, Dumitru,
"Show and tell: A neural image caption generator,"
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015, pp. 3156-3164.
google scholar
 
[reed2016generative] Reed, Scott, Akata, Zeynep, Yan, Xinchen, Logeswaran, Lajanugen, Schiele, Bernt, Lee, Honglak,
"Generative adversarial text to image synthesis,"
Proceedings of The 33rd International Conference on Machine Learning, 3, 2016.
google scholar
 
[krause2016hierarchical] Krause, Jonathan, Johnson, Justin, Krishna, Ranjay, Fei-Fei, Li,
"A Hierarchical Approach for Generating Descriptive Image Paragraphs,"
arXiv preprint arXiv:1611.06607, 2016.
google scholar
 
[dai2017towards] Dai, Bo, Lin, Dahua, Urtasun, Raquel, Fidler, Sanja,
"Towards Diverse and Natural Image Descriptions via a Conditional GAN,"
arXiv preprint arXiv:1703.06029, 2017.
google scholar
 
[donahue2015long] Donahue, Jeffrey, Anne Hendricks, Lisa, Guadarrama, Sergio, Rohrbach, Marcus, Venugopalan, Subhashini, Saenko, Kate, Darrell, Trevor,
"Long-term recurrent convolutional networks for visual recognition and description,"
Proceedings of the IEEE conference on computer vision and pattern recognition, 2015, pp. 2625-2634.
google scholar
 


Deep Learning for Image Manipulation, Computational Photography and Animation

[levine2012continuous] Levine, Sergey, Wang, Jack M, Haraux, Alexis, Popovi\'c, Zoran, Koltun, Vladlen,
"Continuous character control with low-dimensional embeddings,"
ACM Transactions on Graphics (TOG), 31, 4, ACM, 2012, pp. 28.
google scholar
 
[zhu2016generative] Zhu, Jun-Yan, Kr\"ahenb\"uhl, Philipp, Shechtman, Eli, Efros, Alexei A,
"Generative visual manipulation on the natural image manifold,"
European Conference on Computer Vision, 2016, pp. 597-613.
google scholar
 
[upchurch2016deep] Upchurch, Paul, Gardner, Jacob, Bala, Kavita, Pless, Robert, Snavely, Noah, Weinberger, Kilian,
"Deep Feature Interpolation for Image Content Changes,"
arXiv preprint arXiv:1611.05507, 2016.
google scholar
 
[flynn2016deepstereo] Flynn, John, Neulander, Ivan, Philbin, James, Snavely, Noah,
"DeepStereo: Learning to predict new views from the world's imagery,"
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 5515-5524.
google scholar
 
[mordatch2015interactive] Mordatch, Igor, Lowrey, Kendall, Andrew, Galen, Popovic, Zoran, Todorov, Emanuel V,
"Interactive control of diverse complex characters with neural networks,"
Advances in Neural Information Processing Systems, 2015, pp. 3132-3140.
google scholar
 
[isola2016image] Isola, Phillip, Zhu, Jun-Yan, Zhou, Tinghui, Efros, Alexei A,
"Image-to-image translation with conditional adversarial networks,"
arXiv preprint arXiv:1611.07004, 2016.
paper arXiv project code abstract summary google scholar
 
[zhang2016colorful] Zhang, Richard, Isola, Phillip, Efros, Alexei A,
"Colorful image colorization,"
European Conference on Computer Vision, 2016, pp. 649-666.
google scholar
 


Recurrent Neural Networks and Memory

[srivastava2015unsupervised] Srivastava, Nitish, Mansimov, Elman, Salakhutdinov, Ruslan,
"Unsupervised Learning of Video Representations using LSTMs.,"
ICML, 2015, pp. 843-852.
google scholar
 
[byeon2015scene] Byeon, Wonmin, Breuel, Thomas M, Raue, Federico, Liwicki, Marcus,
"Scene labeling with lstm recurrent neural networks,"
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015, pp. 3547-3555.
google scholar
 
[donahue2015long] Donahue, Jeffrey, Anne Hendricks, Lisa, Guadarrama, Sergio, Rohrbach, Marcus, Venugopalan, Subhashini, Saenko, Kate, Darrell, Trevor,
"Long-term recurrent convolutional networks for visual recognition and description,"
Proceedings of the IEEE conference on computer vision and pattern recognition, 2015, pp. 2625-2634.
google scholar
 
[oord2016pixel] Oord, Aaron van den, Kalchbrenner, Nal, Kavukcuoglu, Koray,
"Pixel recurrent neural networks,"
arXiv preprint arXiv:1601.06759, 2016.
google scholar
 
[krause2016hierarchical] Krause, Jonathan, Johnson, Justin, Krishna, Ranjay, Fei-Fei, Li,
"A Hierarchical Approach for Generating Descriptive Image Paragraphs,"
arXiv preprint arXiv:1611.06607, 2016.
google scholar
 
[dai2017towards] Dai, Bo, Lin, Dahua, Urtasun, Raquel, Fidler, Sanja,
"Towards Diverse and Natural Image Descriptions via a Conditional GAN,"
arXiv preprint arXiv:1703.06029, 2017.
google scholar
 


Learning for Robotic Manipulation

[saxena2008robotic] Saxena, Ashutosh, Driemeyer, Justin, Ng, Andrew Y,
"Robotic grasping of novel objects using vision,"
The International Journal of Robotics Research, 27, 2, Sage Publications Sage UK: London, England, 2008, pp. 157-173.
google scholar
 
[sung2015robobarista] Sung, Jaeyong, Jin, Seok Hyun, Saxena, Ashutosh,
"Robobarista: Object part based transfer of manipulation trajectories from crowd-sourcing in 3d pointclouds,"
arXiv preprint arXiv:1504.03071, 2015.
google scholar
 
[misra2016tell] Misra, Dipendra K, Sung, Jaeyong, Lee, Kevin, Saxena, Ashutosh,
"Tell me Dave: Context-sensitive grounding of natural language to manipulation instructions,"
The International Journal of Robotics Research, 35, 1-3, SAGE Publications Sage UK: London, England, 2016, pp. 281-300.
google scholar
 
[lenz2015deep] Lenz, Ian, Lee, Honglak, Saxena, Ashutosh,
"Deep learning for detecting robotic grasps,"
The International Journal of Robotics Research, 34, 4-5, SAGE Publications Sage UK: London, England, 2015, pp. 705-724.
paper video project code data google scholar
 
[lenz2015deepmpc] Lenz, Ian, Knepper, Ross A, Saxena, Ashutosh,
"DeepMPC: Learning Deep Latent Features for Model Predictive Control.,"
Robotics: Science and Systems, 2015.
google scholar
 
[levine2016end] Levine, Sergey, Finn, Chelsea, Darrell, Trevor, Abbeel, Pieter,
"End-to-end training of deep visuomotor policies,"
Journal of Machine Learning Research, 17, 39, 2016, pp. 1-40.
google scholar
 
[levine2015learning] Levine, Sergey, Wagener, Nolan, Abbeel, Pieter,
"Learning contact-rich manipulation skills with guided policy search,"
Robotics and Automation (ICRA), 2015 IEEE International Conference on, 2015, pp. 156-163.
google scholar
 
[pinto2016curious] Pinto, Lerrel, Gandhi, Dhiraj, Han, Yuanfeng, Park, Yong-Lae, Gupta, Abhinav,
"The curious robot: Learning visual representations via physical interactions,"
European Conference on Computer Vision, 2016, pp. 3-18.
paper arXiv google scholar
 
[finn2016deepautoencoders] Finn, Chelsea, Tan, Xin Yu, Duan, Yan, Darrell, Trevor, Levine, Sergey, Abbeel, Pieter,
"Deep spatial autoencoders for visuomotor learning,"
Robotics and Automation (ICRA), 2016 IEEE International Conference on, 2016, pp. 512-519.
google scholar
 
[pinto2016supersizing] Pinto, Lerrel, Gupta, Abhinav,
"Supersizing self-supervision: Learning to grasp from 50k tries and 700 robot hours,"
Robotics and Automation (ICRA), 2016 IEEE International Conference on, 2016, pp. 3406-3413.
paper arXiv google scholar
 
[45450] Sergey Levine, Peter Pastor Sampedro, Alex Krizhevsky, Deirdre Quillen,
"Learning Hand-Eye Coordination for Robotic Grasping with Deep Learning and Large-Scale Data Collection,"
2016.
google scholar
 
[zeng2016multi] Zeng, Andy, Yu, Kuan-Ting, Song, Shuran, Suo, Daniel, Walker Jr, Ed, Rodriguez, Alberto, Xiao, Jianxiong,
"Multi-view Self-supervised Deep Learning for 6D Pose Estimation in the Amazon Picking Challenge,"
arXiv preprint arXiv:1609.09475, 2016.
google scholar
 
[finn2016guided] Finn, Chelsea, Levine, Sergey, Abbeel, Pieter,
"Guided cost learning: Deep inverse optimal control via policy optimization,"
Proceedings of the 33rd International Conference on Machine Learning, 48, 2016.
google scholar
 
[pinto2017supervision] Lerrel Pinto, James Davidson, Abhinav Gupta,
"Supervision via Competition: Robot Adversaries for Learning Tasks,"
2017.
paper video arXiv code google scholar
 


Learning for Autonomous Driving

[janai2017computer] Janai, Joel, G\"uney, Fatma, Behl, Aseem, Geiger, Andreas,
"Computer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art,"
arXiv preprint arXiv:1704.05519, 2017.
paper google scholar
 
[thrun2006stanley] Thrun, Sebastian, Montemerlo, Mike, Dahlkamp, Hendrik, Stavens, David, Aron, Andrei, Diebel, James, Fong, Philip, Gale, John, Halpenny, Morgan, Hoffmann, Gabriel, others,
"Stanley: The robot that won the DARPA Grand Challenge,"
Journal of field Robotics, 23, 9, Wiley Online Library, 2006, pp. 661-692.
google scholar
 
[urmson2007tartan] Urmson, Chris, Bagnell, J Andrew, Baker, Christopher R, Hebert, Martial, Kelly, Alonzo, Rajkumar, Raj, Rybski, Paul E, Scherer, Sebastian, Simmons, Reid, Singh, Sanjiv, others,
"Tartan racing: A multi-modal approach to the darpa urban challenge,"
2007.
google scholar
 
[fletcher2008cornell] Fletcher, Luke, Teller, Seth, Olson, Edwin, Moore, David, Kuwata, Yoshiaki, How, Jonathan, Leonard, John, Miller, Isaac, Campbell, Mark, Huttenlocher, Dan, others,
"The MIT-Cornell collision and why it happened,"
Journal of Field Robotics, 25, 10, Wiley Online Library, 2008, pp. 775-807.
google scholar
 
[leonard2008perception] Leonard, John, How, Jonathan, Teller, Seth, Berger, Mitch, Campbell, Stefan, Fiore, Gaston, Fletcher, Luke, Frazzoli, Emilio, Huang, Albert, Karaman, Sertac, others,
"A perception-driven autonomous urban vehicle,"
Journal of Field Robotics, 25, 10, Wiley Online Library, 2008, pp. 727-774.
google scholar
 
[hadsell2008deep] Hadsell, Raia, Erkan, Ayse, Sermanet, Pierre, Scoffier, Marco, Muller, Urs, LeCun, Yann,
"Deep belief net learning in a long-range vision system for autonomous off-road driving,"
Intelligent Robots and Systems, 2008. IROS 2008. IEEE/RSJ International Conference on, 2008, pp. 628-633.
google scholar
 
[urmson2008autonomous] Urmson, Chris, Anhalt, Joshua, Bagnell, Drew, Baker, Christopher, Bittner, Robert, Clark, MN, Dolan, John, Duggins, Dave, Galatali, Tugrul, Geyer, Chris, others,
"Autonomous driving in urban environments: Boss and the urban challenge,"
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[petrovskaya2009model] Petrovskaya, Anna, Thrun, Sebastian,
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[dolgov2010path] Dolgov, Dmitri, Thrun, Sebastian, Montemerlo, Michael, Diebel, James,
"Path planning for autonomous vehicles in unknown semi-structured environments,"
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[levinson2010robust] Levinson, Jesse, Thrun, Sebastian,
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[levinson2011towards] Levinson, Jesse, Askeland, Jake, Becker, Jan, Dolson, Jennifer, Held, David, Kammel, Soeren, Kolter, J Zico, Langer, Dirk, Pink, Oliver, Pratt, Vaughan, others,
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[geiger2012we] Geiger, Andreas, Lenz, Philip, Urtasun, Raquel,
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[cirecsan2012multi] Cire\csAn, Dan, Meier, Ueli, Masci, Jonathan, Schmidhuber, J\"urgen,
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[huval2015empirical] Huval, Brody, Wang, Tao, Tandon, Sameep, Kiske, Jeff, Song, Will, Pazhayampallil, Joel, Andriluka, Mykhaylo, Rajpurkar, Pranav, Migimatsu, Toki, Cheng-Yue, Royce, others,
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[chen2015deepdriving] Chen, Chenyi, Seff, Ari, Kornhauser, Alain, Xiao, Jianxiong,
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[teichmann2016multinet] Teichmann, Marvin, Weber, Michael, Zoellner, Marius, Cipolla, Roberto, Urtasun, Raquel,
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[seff2016learning] Seff, Ari, Xiao, Jianxiong,
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[xu2016end] Xu, Huazhe, Gao, Yang, Yu, Fisher, Darrell, Trevor,
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[bojarski2016end] Bojarski, Mariusz, Del Testa, Davide, Dworakowski, Daniel, Firner, Bernhard, Flepp, Beat, Goyal, Prasoon, Jackel, Lawrence D, Monfort, Mathew, Muller, Urs, Zhang, Jiakai, others,
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[zhang2016query] Zhang, Jiakai, Cho, Kyunghyun,
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[provodin2016fast] Provodin, Artem, Torabi, Liila, Flepp, Beat, LeCun, Yann, Sergio, Michael, Jackel, LD, Muller, Urs, Zbontar, Jure,
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Learning for Robotic Control

[bagnell2001autonomous] Bagnell, J Andrew, Schneider, Jeff G,
"Autonomous helicopter control using reinforcement learning policy search methods,"
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[tedrake2004stochastic] Tedrake, Russ, Zhang, Teresa Weirui, Seung, H Sebastian,
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[abbeel2007application] Abbeel, Pieter, Coates, Adam, Quigley, Morgan, Ng, Andrew Y,
"An application of reinforcement learning to aerobatic helicopter flight,"
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[abbeel2010autonomous] Abbeel, Pieter, Coates, Adam, Ng, Andrew Y,
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[zhang2016learning] Zhang, Marvin, McCarthy, Zoe, Finn, Chelsea, Levine, Sergey, Abbeel, Pieter,
"Learning deep neural network policies with continuous memory states,"
Robotics and Automation (ICRA), 2016 IEEE International Conference on, 2016, pp. 520-527.
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[lee2017learning] Lee, Alex X, Levine, Sergey, Abbeel, Pieter,
"Learning Visual Servoing with Deep Features and Fitted Q-Iteration,"
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[kahn2017uncertainty] Kahn, Gregory, Villaflor, Adam, Pong, Vitchyr, Abbeel, Pieter, Levine, Sergey,
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[bills2011autonomous] Bills, Cooper, Chen, Joyce, Saxena, Ashutosh,
"Autonomous MAV flight in indoor environments using single image perspective cues,"
Robotics and automation (ICRA), 2011 IEEE international conference on, 2011, pp. 5776-5783.
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[fraundorfer2012vision] Fraundorfer, Friedrich, Heng, Lionel, Honegger, Dominik, Lee, Gim Hee, Meier, Lorenz, Tanskanen, Petri, Pollefeys, Marc,
"Vision-based autonomous mapping and exploration using a quadrotor MAV,"
Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on, 2012, pp. 4557-4564.
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[tellex2011understanding] Tellex, Stefanie A, Kollar, Thomas Fleming, Dickerson, Steven R, Walter, Matthew R, Banerjee, Ashis, Teller, Seth, Roy, Nicholas,
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[tellex2014asking] Tellex, Stefanie, Knepper, Ross A, Li, Adrian, Rus, Daniela, Roy, Nicholas,
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[daftry2016learning] Daftry, Shreyansh, Bagnell, J Andrew, Hebert, Martial,
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Learning from Physics

[lerer2016learning] Lerer, Adam, Gross, Sam, Fergus, Rob,
"Learning physical intuition of block towers by example,"
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[finn2016unsupervised] Finn, Chelsea, Goodfellow, Ian, Levine, Sergey,
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[pinto2016curious] Pinto, Lerrel, Gandhi, Dhiraj, Han, Yuanfeng, Park, Yong-Lae, Gupta, Abhinav,
"The curious robot: Learning visual representations via physical interactions,"
European Conference on Computer Vision, 2016, pp. 3-18.
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[agrawal2016learning] Agrawal, Pulkit, Nair, Ashvin, Abbeel, Pieter, Malik, Jitendra, Levine, Sergey,
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[fragkiadaki2015learning] Fragkiadaki, Katerina, Agrawal, Pulkit, Levine, Sergey, Malik, Jitendra,
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[kulkarni2015deep] Kulkarni, Tejas D, Whitney, William F, Kohli, Pushmeet, Tenenbaum, Josh,
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[kingma2013auto] Kingma, Diederik P, Welling, Max,
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arXiv preprint arXiv:1312.6114, 2013.
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Advanced Reinforcement Learning

[abbeel2004apprenticeship] Abbeel, Pieter, Ng, Andrew Y,
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[ross2011reduction] Ross, St\'ephane, Gordon, Geoffrey J, Bagnell, Drew,
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[ziebart2008maximum] Ziebart, Brian D, Maas, Andrew L, Bagnell, J Andrew, Dey, Anind K,
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[wulfmeier2015maximum] Wulfmeier, Markus, Ondruska, Peter, Posner, Ingmar,
"Maximum entropy deep inverse reinforcement learning,"
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[finn2016guided] Finn, Chelsea, Levine, Sergey, Abbeel, Pieter,
"Guided cost learning: Deep inverse optimal control via policy optimization,"
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[ho2016generative] Ho, Jonathan, Ermon, Stefano,
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arXiv preprint arXiv:1604.07316, 2016.
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[zhang2016query] Zhang, Jiakai, Cho, Kyunghyun,
"Query-efficient imitation learning for end-to-end autonomous driving,"
arXiv preprint arXiv:1605.06450, 2016.
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[schaul2015prioritized] Schaul, Tom, Quan, John, Antonoglou, Ioannis, Silver, David,
"Prioritized experience replay,"
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[wang2015dueling] Wang, Ziyu, Schaul, Tom, Hessel, Matteo, van Hasselt, Hado, Lanctot, Marc, de Freitas, Nando,
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[levine2013guided] Levine, Sergey, Koltun, Vladlen,
"Guided Policy Search.,"
ICML (3), 2013, pp. 1-9.
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[levine2014learning] Levine, Sergey, Koltun, Vladlen,
"Learning Complex Neural Network Policies with Trajectory Optimization.,"
ICML, 2014, pp. 829-837.
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[levine2014learning] Levine, Sergey, Koltun, Vladlen,
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[montgomery2016guided] Montgomery, William H, Levine, Sergey,
"Guided Policy Search via Approximate Mirror Descent,"
Advances in Neural Information Processing Systems, 2016, pp. 4008-4016.
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[zhang2016learning] Zhang, Marvin, McCarthy, Zoe, Finn, Chelsea, Levine, Sergey, Abbeel, Pieter,
"Learning deep neural network policies with continuous memory states,"
Robotics and Automation (ICRA), 2016 IEEE International Conference on, 2016, pp. 520-527.
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[finn2016deepautoencoders] Finn, Chelsea, Tan, Xin Yu, Duan, Yan, Darrell, Trevor, Levine, Sergey, Abbeel, Pieter,
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[schulman2015trust] Schulman, John, Levine, Sergey, Abbeel, Pieter, Jordan, Michael I, Moritz, Philipp,
"Trust Region Policy Optimization.,"
ICML, 2015, pp. 1889-1897.
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[lillicrap2015continuous] Lillicrap, Timothy P, Hunt, Jonathan J, Pritzel, Alexander, Heess, Nicolas, Erez, Tom, Tassa, Yuval, Silver, David, Wierstra, Daan,
"Continuous control with deep reinforcement learning,"
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[duan2016benchmarking] Duan, Yan, Chen, Xi, Houthooft, Rein,
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[tamar2016value] Tamar, Aviv, Wu, Yi, Thomas, Garrett, Levine, Sergey, Abbeel, Pieter,
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[finn2016deepforesight] Finn, Chelsea, Levine, Sergey,
"Deep Visual Foresight for Planning Robot Motion,"
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[chebotar2017combining] Chebotar, Yevgen, Hausman, Karol, Zhang, Marvin, Sukhatme, Gaurav, Schaal, Stefan, Levine, Sergey,
"Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning,"
arXiv preprint arXiv:1703.03078, 2017.
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[gu2016q] Gu, Shixiang, Lillicrap, Timothy, Ghahramani, Zoubin, Turner, Richard E, Levine, Sergey,
"Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic,"
arXiv preprint arXiv:1611.02247, 2016.
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[o2016pgq] O'Donoghue, Brendan, Munos, Remi, Kavukcuoglu, Koray, Mnih, Volodymyr,
"PGQ: Combining policy gradient and Q-learning,"
arXiv preprint arXiv:1611.01626, 2016.
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[bahdanau2016actor] Bahdanau, Dzmitry, Brakel, Philemon, Xu, Kelvin, Goyal, Anirudh, Lowe, Ryan, Pineau, Joelle, Courville, Aaron, Bengio, Yoshua,
"An actor-critic algorithm for sequence prediction,"
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[jaderberg2016reinforcement] Jaderberg, Max, Mnih, Volodymyr, Czarnecki, Wojciech Marian, Schaul, Tom, Leibo, Joel Z, Silver, David, Kavukcuoglu, Koray,
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arXiv preprint arXiv:1611.05397, 2016.
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Miscellaneous

[choy20163d] Choy, Christopher B, Xu, Danfei, Gwak, JunYoung, Chen, Kevin, Savarese, Silvio,
"3D-R2N2: A unified approach for single and multi-view 3d object reconstruction,"
European Conference on Computer Vision, 2016, pp. 628-644.
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