MoDeep: A Deep Learning Framework Using Motion Features for Human Pose Estimation. - Arjun Jain; Jonathan Tompson; Yann LeCun; Christoph Bregler (ACCV (2), 2014)

Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation. - Jonathan Tompson; Arjun Jain; Yann LeCun; Christoph Bregler (NIPS, 2014)

Learning Human Pose Estimation Features with Convolutional Networks. - Arjun Jain; Jonathan Tompson; Mykhaylo Andriluka; Graham W. Taylor; Christoph Bregler (ICLR (Poster), 2014)

Real-Time Continuous Pose Recovery of Human Hands Using Convolutional Networks. - Jonathan Tompson; Murphy Stein; Yann LeCun; Ken Perlin (ACM Trans. Graph., 2014)

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 (CVPR, 2015)

Efficient object localization using Convolutional Networks. - Jonathan Tompson; Ross Goroshin; Arjun Jain; Yann LeCun; Christoph Bregler (CVPR, 2015)

Unsupervised Learning of Spatiotemporally Coherent Metrics. - Ross Goroshin; Joan Bruna; Jonathan Tompson; David Eigen; Yann LeCun (ICCV, 2015)

Unsupervised Feature Learning from Temporal Data. - Ross Goroshin; Joan Bruna; Jonathan Tompson; David Eigen; Yann LeCun (ICLR (Workshop), 2015)

Localization of Humans in Images Using Convolutional Networks. - Jonathan Tompson (2015)

Learning Robotic Manipulation of Granular Media. - Connor Schenck; Jonathan Tompson; Sergey Levine; Dieter Fox (CoRL, 2017)

Towards Accurate Multi-person Pose Estimation in the Wild. - George Papandreou; Tyler Zhu; Nori Kanazawa; Alexander Toshev; Jonathan Tompson; Chris Bregler; Kevin Murphy 002 (CVPR, 2017)

Accelerating Eulerian Fluid Simulation With Convolutional Networks. - Jonathan Tompson; Kristofer Schlachter; Pablo Sprechmann; Ken Perlin (ICML, 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)

Temporal Reasoning in Videos Using Convolutional Gated Recurrent Units. - Debidatta Dwibedi; Pierre Sermanet; Jonathan Tompson (CVPR Workshops, 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 002 (ECCV (14), 2018)

Learning Actionable Representations from Visual Observations. - Debidatta Dwibedi; Jonathan Tompson; Corey Lynch; Pierre Sermanet (IROS, 2018)

Discovery of Latent 3D Keypoints via End-to-end Geometric Reasoning. - Supasorn Suwajanakorn; Noah Snavely; Jonathan Tompson; Mohammad Norouzi 002 (NeurIPS, 2018)

Addressing Sample Inefficiency and Reward Bias in Inverse Reinforcement Learning. - Ilya Kostrikov; Kumar Krishna Agrawal; Sergey Levine; Jonathan Tompson (CoRR, 2018)

Learning Latent Plans from Play. - Corey Lynch; Mohi Khansari; Ted Xiao; Vikash Kumar; Jonathan Tompson; Sergey Levine; Pierre Sermanet (CoRL, 2019)

Temporal Cycle-Consistency Learning. - Debidatta Dwibedi; Yusuf Aytar; Jonathan Tompson; Pierre Sermanet; Andrew Zisserman (CVPR, 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 (ICLR (Poster), 2019)

Beyond Photo Realism for Domain Adaptation from Synthetic Data. - Kristofer Schlachter; Connor DeFanti; Sebastian Herscher; Ken Perlin; Jonathan Tompson (CoRR, 2019)

Transporter Networks: Rearranging the Visual World for Robotic Manipulation. - Andy Zeng 001; Pete Florence; Jonathan Tompson; Stefan Welker; Jonathan Chien; Maria Attarian; Travis Armstrong; Ivan Krasin; Dan Duong; Vikas Sindhwani; Johnny Lee (CoRL, 2020)

Counting Out Time: Class Agnostic Video Repetition Counting in the Wild. - Debidatta Dwibedi; Yusuf Aytar; Jonathan Tompson; Pierre Sermanet; Andrew Zisserman (CVPR, 2020)

Imitation Learning via Off-Policy Distribution Matching. - Ilya Kostrikov; Ofir Nachum; Jonathan Tompson (ICLR, 2020)

An Analysis of Object Representations in Deep Visual Trackers. - Ross Goroshin; Jonathan Tompson; Debidatta Dwibedi (CoRR, 2020)

ADAIL: Adaptive Adversarial Imitation Learning. - Yiren Lu 001; Jonathan Tompson (CoRR, 2020)

Implicit Behavioral Cloning. - Pete Florence; Corey Lynch; Andy Zeng 001; Oscar A. Ramirez; Ayzaan Wahid; Laura Downs; Adrian Wong; Johnny Lee; Igor Mordatch; Jonathan Tompson (CoRL, 2021)

XIRL: Cross-embodiment Inverse Reinforcement Learning. - Kevin Zakka; Andy Zeng 001; Pete Florence; Jonathan Tompson; Jeannette Bohg; Debidatta Dwibedi (CoRL, 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 (ICCV, 2021)

Offline Reinforcement Learning with Fisher Divergence Critic Regularization. - Ilya Kostrikov; Rob Fergus; Jonathan Tompson; Ofir Nachum (ICML, 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 001 (ICRA, 2021)

Inner Monologue: Embodied Reasoning through Planning with Language Models. - Wenlong Huang; Fei Xia 002; Ted Xiao; Harris Chan; Jacky Liang; Pete Florence; Andy Zeng 001; Jonathan Tompson; Igor Mordatch; Yevgen Chebotar; Pierre Sermanet; Tomas Jackson; et al. (CoRL, 2022)

Improving Zero-Shot Generalization in Offline Reinforcement Learning using Generalized Similarity Functions. - Bogdan Mazoure; Ilya Kostrikov; Ofir Nachum; Jonathan Tompson (NeurIPS, 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)

Geometry Matching for Multi-Embodiment Grasping. - Maria Attarian; Muhammad Adil Asif; Jingzhou Liu; Ruthrash Hari; Animesh Garg; Igor Gilitschenski; Jonathan Tompson (CoRL, 2023)

Contrastive Value Learning: Implicit Models for Simple Offline RL. - Bogdan Mazoure; Benjamin Eysenbach; Ofir Nachum; Jonathan Tompson (CoRL, 2023)

PaLM-E: An Embodied Multimodal Language Model. - Danny Driess; Fei Xia 002; Mehdi S. M. Sajjadi; Corey Lynch; Aakanksha Chowdhery; Brian Ichter; Ayzaan Wahid; Jonathan Tompson; Quan Vuong; Tianhe Yu; Wenlong Huang; Yevgen Chebotar; et al. (ICML, 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 (ICRA, 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 (Robotics: Science and Systems, 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; et al. (Robotics: Science and Systems, 2023)

Learning Interactive Real-World Simulators. - Mengjiao Yang 001; Yilun Du; Kamyar Ghasemipour; Jonathan Tompson; Dale Schuurmans; Pieter Abbeel (CoRR, 2023)

ALOHA Unleashed: A Simple Recipe for Robot Dexterity. - Tony Z. Zhao; Jonathan Tompson; Danny Driess; Pete Florence; Seyed Kamyar Seyed Ghasemipour; Chelsea Finn; Ayzaan Wahid (CoRL, 2024)

Video Language Planning. - Yilun Du; Sherry Yang 001; Pete Florence; Fei Xia 002; Ayzaan Wahid; Brian Ichter; Pierre Sermanet; Tianhe Yu; Pieter Abbeel; Joshua B. Tenenbaum; Leslie Pack Kaelbling; Andy Zeng 001; et al. (ICLR, 2024)

Learning Interactive Real-World Simulators. - Sherry Yang 001; Yilun Du; Seyed Kamyar Seyed Ghasemipour; Jonathan Tompson; Leslie Pack Kaelbling; Dale Schuurmans; Pieter Abbeel (ICLR, 2024)

Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration. - Abby O'Neill; Abdul Rehman; Abhiram Maddukuri; Abhishek Gupta 004; Abhishek Padalkar; Abraham Lee; Acorn Pooley; Agrim Gupta; Ajay Mandlekar; Ajinkya Jain; Albert Tung; Alex Bewley; et al. (ICRA, 2024)

FlexCap: Describe Anything in Images in Controllable Detail. - Debidatta Dwibedi; Vidhi Jain; Jonathan Tompson; Andrew Zisserman; Yusuf Aytar (NeurIPS, 2024)

RT-H: Action Hierarchies using Language. - Suneel Belkhale; Tianli Ding; Ted Xiao; Pierre Sermanet; Quan Vuong; Jonathan Tompson; Yevgen Chebotar; Debidatta Dwibedi; Dorsa Sadigh (Robotics: Science and Systems, 2024)

Learning to Learn Faster from Human Feedback with Language Model Predictive Control. - Jacky Liang; Fei Xia 002; Wenhao Yu 003; Andy Zeng 001; Maria Attarian; Maria Bauzá Villalonga; Matthew Bennice; Alex Bewley; Adil Dostmohamed; Chuyuan Fu; Nimrod Gileadi; Marissa Giustina; et al. (Robotics: Science and Systems, 2024)

Learning to Learn Faster from Human Feedback with Language Model Predictive Control. - Jacky Liang; Fei Xia 002; Wenhao Yu 003; Andy Zeng 001; Montserrat Gonzalez Arenas; Maria Attarian; Maria Bauzá 001; Matthew Bennice; Alex Bewley; Adil Dostmohamed; Chuyuan Kelly Fu; Nimrod Gileadi; et al. (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)

FlexCap: Generating Rich, Localized, and Flexible Captions in Images. - Debidatta Dwibedi; Vidhi Jain; Jonathan Tompson; Andrew Zisserman; Yusuf Aytar (CoRR, 2024)

ALOHA 2: An Enhanced Low-Cost Hardware for Bimanual Teleoperation. - ALOHA 2 Team; Jorge Aldaco; Travis Armstrong; Robert Baruch; Jeff Bingham; Sanky Chan; Kenneth Draper; Debidatta Dwibedi; Chelsea Finn; Pete Florence; Spencer Goodrich; Wayne Gramlich; et al. (CoRR, 2024)

OVR: A Dataset for Open Vocabulary Temporal Repetition Counting in Videos. - Debidatta Dwibedi; Yusuf Aytar; Jonathan Tompson; Andrew Zisserman (CoRR, 2024)

Vision Language Models are In-Context Value Learners. - Yecheng Jason Ma; Joey Hejna; Ayzaan Wahid; Chuyuan Fu; Dhruv Shah; Jacky Liang; Zhuo Xu; Sean Kirmani; Peng Xu 010; Danny Driess; Ted Xiao; Jonathan Tompson; et al. (CoRR, 2024)

A Short Note on Evaluating RepNet for Temporal Repetition Counting in Videos. - Debidatta Dwibedi; Yusuf Aytar; Jonathan Tompson; Pierre Sermanet; Andrew Zisserman (CoRR, 2024)

Learning the RoPEs: Better 2D and 3D Position Encodings with STRING. - Connor Schenck; Isaac Reid; Mithun George Jacob; Alex Bewley; Joshua Ainslie; David Rendleman; Deepali Jain; Mohit Sharma 001; Avinava Dubey; Ayzaan Wahid; Sumeet Singh; René Wagner; et al. (CoRR, 2025)

Robot Data Curation with Mutual Information Estimators. - Joey Hejna; Suvir Mirchandani; Ashwin Balakrishna; Annie Xie; Ayzaan Wahid; Jonathan Tompson; Pannag Sanketi; Dhruv Shah; Coline Devin; Dorsa Sadigh (CoRR, 2025)

Gemini Robotics: Bringing AI into the Physical World. - Gemini Robotics Team; Saminda Abeyruwan; Joshua Ainslie; Jean-Baptiste Alayrac; Montserrat Gonzalez Arenas; Travis Armstrong; Ashwin Balakrishna; Robert Baruch; Maria Bauzá 001; Michiel Blokzijl; Steven Bohez; Konstantinos Bousmalis; et al. (CoRR, 2025)