Jonathan Tompson

According to our database, Jonathan Tompson authored at least 46 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

FlexCap: Generating Rich, Localized, and Flexible Captions in Images.

Debidatta Dwibedi, Vidhi Jain, Jonathan Tompson, Andrew Zisserman, Yusuf Aytar

CoRR, 2024

RT-H: Action Hierarchies Using Language.

Suneel Belkhale, Tianli Ding, Ted Xiao, Pierre Sermanet, Quon Vuong, Jonathan Tompson, Yevgen Chebotar, Debidatta Dwibedi, Dorsa Sadigh

CoRR, 2024

Learning to Learn Faster from Human Feedback with Language Model Predictive Control.

Jacky Liang, Fei Xia, Wenhao Yu, Andy Zeng, Montserrat Gonzalez Arenas, Maria Attarian, Maria Bauzá, Matthew Bennice, Alex Bewley, Adil Dostmohamed, Chuyuan Kelly Fu, Nimrod Gileadi, Marissa Giustina, Keerthana Gopalakrishnan, Leonard Hasenclever, Jan Humplik, Jasmine Hsu, Nikhil J. Joshi, Ben Jyenis, J. Chase Kew, Sean Kirmani, Tsang-Wei Edward Lee, Kuang-Huei Lee, Assaf Hurwitz Michaely, Joss Moore, Ken Oslund, Dushyant Rao, Allen Z. Ren, Baruch Tabanpour, Quan Vuong, Ayzaan Wahid, Ted Xiao, Ying Xu, Vincent Zhuang, Peng Xu, Erik Frey, Ken Caluwaerts, Tingnan Zhang, Brian Ichter, Jonathan Tompson, Leila Takayama, Vincent Vanhoucke, Izhak Shafran, Maja J. Mataric, Dorsa Sadigh, Nicolas Heess, Kanishka Rao, Nik Stewart, Jie Tan, Carolina Parada

CoRR, 2024

2023

Video Language Planning.

Yilun Du, Mengjiao Yang, Pete Florence, Fei Xia, Ayzaan Wahid, Brian Ichter, Pierre Sermanet, Tianhe Yu, Pieter Abbeel, Joshua B. Tenenbaum, Leslie Pack Kaelbling, Andy Zeng, Jonathan Tompson

CoRR, 2023

Learning Interactive Real-World Simulators.

Mengjiao Yang, Yilun Du, Kamyar Ghasemipour, Jonathan Tompson, Dale Schuurmans, Pieter Abbeel

CoRR, 2023

Scaling Robot Learning with Semantically Imagined Experience.

Tianhe Yu, Ted Xiao, Jonathan Tompson, Austin Stone, Su Wang, Anthony Brohan, Jaspiar Singh, Clayton Tan, Dee M, Jodilyn Peralta, Karol Hausman, Brian Ichter, Fei Xia

Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

Robotic Skill Acquisition via Instruction Augmentation with Vision-Language Models.

Ted Xiao, Harris Chan, Pierre Sermanet, Ayzaan Wahid, Anthony Brohan, Karol Hausman, Sergey Levine, Jonathan Tompson

Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

Visuomotor Control in Multi-Object Scenes Using Object-Aware Representations.

Negin Heravi, Ayzaan Wahid, Corey Lynch, Pete Florence, Travis Armstrong, Jonathan Tompson, Pierre Sermanet, Jeannette Bohg, Debidatta Dwibedi

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

PaLM-E: An Embodied Multimodal Language Model.

Danny Driess, Fei Xia, Mehdi S. M. Sajjadi, Corey Lynch, Aakanksha Chowdhery, Brian Ichter, Ayzaan Wahid, Jonathan Tompson, Quan Vuong, Tianhe Yu, Wenlong Huang, Yevgen Chebotar, Pierre Sermanet, Daniel Duckworth, Sergey Levine, Vincent Vanhoucke, Karol Hausman, Marc Toussaint, Klaus Greff, Andy Zeng, Igor Mordatch, Pete Florence

Proceedings of the International Conference on Machine Learning, 2023

Contrastive Value Learning: Implicit Models for Simple Offline RL.

Bogdan Mazoure, Benjamin Eysenbach, Ofir Nachum, Jonathan Tompson

Proceedings of the Conference on Robot Learning, 2023

Geometry Matching for Multi-Embodiment Grasping.

Maria Attarian, Muhammad Adil Asif, Jingzhou Liu, Ruthrash Hari, Animesh Garg, Igor Gilitschenski, Jonathan Tompson

Proceedings of the Conference on Robot Learning, 2023

2022

Interactive Language: Talking to Robots in Real Time.

Corey Lynch, Ayzaan Wahid, Jonathan Tompson, Tianli Ding, James Betker, Robert Baruch, Travis Armstrong, Pete Florence

CoRR, 2022

Improving Zero-Shot Generalization in Offline Reinforcement Learning using Generalized Similarity Functions.

Bogdan Mazoure, Ilya Kostrikov, Ofir Nachum, Jonathan Tompson

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Inner Monologue: Embodied Reasoning through Planning with Language Models.

Wenlong Huang, Fei Xia, Ted Xiao, Harris Chan, Jacky Liang, Pete Florence, Andy Zeng, Jonathan Tompson, Igor Mordatch, Yevgen Chebotar, Pierre Sermanet, Tomas Jackson, Noah Brown, Linda Luu, Sergey Levine, Karol Hausman, Brian Ichter

Proceedings of the Conference on Robot Learning, 2022

2021

Learning to Rearrange Deformable Cables, Fabrics, and Bags with Goal-Conditioned Transporter Networks.

Daniel Seita, Pete Florence, Jonathan Tompson, Erwin Coumans, Vikas Sindhwani, Ken Goldberg, Andy Zeng

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Offline Reinforcement Learning with Fisher Divergence Critic Regularization.

Ilya Kostrikov, Rob Fergus, Jonathan Tompson, Ofir Nachum

Proceedings of the 38th International Conference on Machine Learning, 2021

With a Little Help from My Friends: Nearest-Neighbor Contrastive Learning of Visual Representations.

Debidatta Dwibedi, Yusuf Aytar, Jonathan Tompson, Pierre Sermanet, Andrew Zisserman

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

XIRL: Cross-embodiment Inverse Reinforcement Learning.

Kevin Zakka, Andy Zeng, Pete Florence, Jonathan Tompson, Jeannette Bohg, Debidatta Dwibedi

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

Implicit Behavioral Cloning.

Pete Florence, Corey Lynch, Andy Zeng, Oscar A. Ramirez, Ayzaan Wahid, Laura Downs, Adrian Wong, Johnny Lee, Igor Mordatch, Jonathan Tompson

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020

ADAIL: Adaptive Adversarial Imitation Learning.

Yiren Lu, Jonathan Tompson

CoRR, 2020

An Analysis of Object Representations in Deep Visual Trackers.

Ross Goroshin, Jonathan Tompson, Debidatta Dwibedi

CoRR, 2020

Imitation Learning via Off-Policy Distribution Matching.

Ilya Kostrikov, Ofir Nachum, Jonathan Tompson

Proceedings of the 8th International Conference on Learning Representations, 2020

Counting Out Time: Class Agnostic Video Repetition Counting in the Wild.

Debidatta Dwibedi, Yusuf Aytar, Jonathan Tompson, Pierre Sermanet, Andrew Zisserman

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Transporter Networks: Rearranging the Visual World for Robotic Manipulation.

Andy Zeng, Pete Florence, Jonathan Tompson, Stefan Welker, Jonathan Chien, Maria Attarian, Travis Armstrong, Ivan Krasin, Dan Duong, Vikas Sindhwani, Johnny Lee

Proceedings of the 4th Conference on Robot Learning, 2020

2019

Beyond Photo Realism for Domain Adaptation from Synthetic Data.

Kristofer Schlachter, Connor DeFanti, Sebastian Herscher, Ken Perlin, Jonathan Tompson

CoRR, 2019

Discriminator-Actor-Critic: Addressing Sample Inefficiency and Reward Bias in Adversarial Imitation Learning.

Ilya Kostrikov, Kumar Krishna Agrawal, Debidatta Dwibedi, Sergey Levine, Jonathan Tompson

Proceedings of the 7th International Conference on Learning Representations, 2019

Temporal Cycle-Consistency Learning.

Debidatta Dwibedi, Yusuf Aytar, Jonathan Tompson, Pierre Sermanet, Andrew Zisserman

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Learning Latent Plans from Play.

Corey Lynch, Mohi Khansari, Ted Xiao, Vikash Kumar, Jonathan Tompson, Sergey Levine, Pierre Sermanet

Proceedings of the 3rd Annual Conference on Robot Learning, 2019

2018

Addressing Sample Inefficiency and Reward Bias in Inverse Reinforcement Learning.

Ilya Kostrikov, Kumar Krishna Agrawal, Sergey Levine, Jonathan Tompson

CoRR, 2018

Discovery of Latent 3D Keypoints via End-to-end Geometric Reasoning.

Supasorn Suwajanakorn, Noah Snavely, Jonathan Tompson, Mohammad Norouzi

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning Actionable Representations from Visual Observations.

Debidatta Dwibedi, Jonathan Tompson, Corey Lynch, Pierre Sermanet

Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

PersonLab: Person Pose Estimation and Instance Segmentation with a Bottom-Up, Part-Based, Geometric Embedding Model.

George Papandreou, Tyler Zhu, Liang-Chieh Chen, Spyros Gidaris, Jonathan Tompson, Kevin Murphy

Proceedings of the Computer Vision - ECCV 2018, 2018

Temporal Reasoning in Videos Using Convolutional Gated Recurrent Units.

Debidatta Dwibedi, Pierre Sermanet, Jonathan Tompson

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2018

2017

MARCOnI - ConvNet-Based MARker-Less Motion Capture in Outdoor and Indoor Scenes.

Ahmed Elhayek, Edilson de Aguiar, Arjun Jain, Jonathan Tompson, Leonid Pishchulin, Mykhaylo Andriluka, Christoph Bregler, Bernt Schiele, Christian Theobalt

IEEE Trans. Pattern Anal. Mach. Intell., 2017

Accelerating Eulerian Fluid Simulation With Convolutional Networks.

Jonathan Tompson, Kristofer Schlachter, Pablo Sprechmann, Ken Perlin

Proceedings of the 5th International Conference on Learning Representations, 2017

Towards Accurate Multi-person Pose Estimation in the Wild.

George Papandreou, Tyler Zhu, Nori Kanazawa, Alexander Toshev, Jonathan Tompson, Chris Bregler, Kevin Murphy

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Learning Robotic Manipulation of Granular Media.

Connor Schenck, Jonathan Tompson, Sergey Levine, Dieter Fox

Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017

2015

Localization of Humans in Images Using Convolutional Networks.

Jonathan Tompson

PhD thesis, 2015

Unsupervised Feature Learning from Temporal Data.

Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun

Proceedings of the 3rd International Conference on Learning Representations, 2015

Unsupervised Learning of Spatiotemporally Coherent Metrics.

Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Efficient object localization using Convolutional Networks.

Jonathan Tompson, Ross Goroshin, Arjun Jain, Yann LeCun, Christoph Bregler

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

Efficient ConvNet-based marker-less motion capture in general scenes with a low number of cameras.

Ahmed Elhayek, Edilson de Aguiar, Arjun Jain, Jonathan Tompson, Leonid Pishchulin, Mykhaylo Andriluka, Christoph Bregler, Bernt Schiele, Christian Theobalt

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014

Real-Time Continuous Pose Recovery of Human Hands Using Convolutional Networks.

Jonathan Tompson, Murphy Stein, Yann LeCun, Ken Perlin

ACM Trans. Graph., 2014

Learning Human Pose Estimation Features with Convolutional Networks.

Arjun Jain, Jonathan Tompson, Mykhaylo Andriluka, Graham W. Taylor, Christoph Bregler

Proceedings of the 2nd International Conference on Learning Representations, 2014

Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation.

Jonathan Tompson, Arjun Jain, Yann LeCun, Christoph Bregler

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

MoDeep: A Deep Learning Framework Using Motion Features for Human Pose Estimation.

Arjun Jain, Jonathan Tompson, Yann LeCun, Christoph Bregler

Proceedings of the Computer Vision - ACCV 2014, 2014