Austin Stone

According to our database, Austin Stone authored at least 18 papers between 2017 and 2023.

Collaborative distances:

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

2023

Open-World Object Manipulation using Pre-trained Vision-Language Models.

Austin Stone, Ted Xiao, Yao Lu, Keerthana Gopalakrishnan, Kuang-Huei Lee, Quan Vuong, Paul Wohlhart, Brianna Zitkovich, Fei Xia, Chelsea Finn, Karol Hausman

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

RT-1: Robotics Transformer for Real-World Control at Scale.

Anthony Brohan, Noah Brown, Justice Carbajal, Yevgen Chebotar, Joseph Dabis, Chelsea Finn, Keerthana Gopalakrishnan, Karol Hausman, Alexander Herzog, Jasmine Hsu, Julian Ibarz, Brian Ichter, Alex Irpan, Tomas Jackson, Sally Jesmonth, Nikhil J. Joshi, Ryan Julian, Dmitry Kalashnikov, Yuheng Kuang, Isabel Leal, Kuang-Huei Lee, Sergey Levine, Yao Lu, Utsav Malla, Deeksha Manjunath, Igor Mordatch, Ofir Nachum, Carolina Parada, Jodilyn Peralta, Emily Perez, Karl Pertsch, Jornell Quiambao, Kanishka Rao, Michael S. Ryoo, Grecia Salazar, Pannag R. Sanketi, Kevin Sayed, Jaspiar Singh, Sumedh Sontakke, Austin Stone, Clayton Tan, Huong T. Tran, Vincent Vanhoucke, Steve Vega, Quan Vuong, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Tianhe Yu, Brianna Zitkovich

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

Open-vocabulary Queryable Scene Representations for Real World Planning.

Boyuan Chen, Fei Xia, Brian Ichter, Kanishka Rao, Keerthana Gopalakrishnan, Michael S. Ryoo, Austin Stone, Daniel Kappler

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

Token Turing Machines.

Michael S. Ryoo, Keerthana Gopalakrishnan, Kumara Kahatapitiya, Ted Xiao, Kanishka Rao, Austin Stone, Yao Lu, Julian Ibarz, Anurag Arnab

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Self-supervised AutoFlow.

Hsin-Ping Huang, Charles Herrmann, Junhwa Hur, Erika Lu, Kyle Sargent, Austin Stone, Ming-Hsuan Yang, Deqing Sun

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Open-World Object Manipulation using Pre-Trained Vision-Language Models.

Austin Stone, Ted Xiao, Yao Lu, Keerthana Gopalakrishnan, Kuang-Huei Lee, Quan Vuong, Paul Wohlhart, Sean Kirmani, Brianna Zitkovich, Fei Xia, Chelsea Finn, Karol Hausman

Proceedings of the Conference on Robot Learning, 2023

2022

Simple Open-Vocabulary Object Detection with Vision Transformers.

Matthias Minderer, Alexey A. Gritsenko, Austin Stone, Maxim Neumann, Dirk Weissenborn, Alexey Dosovitskiy, Aravindh Mahendran, Anurag Arnab, Mostafa Dehghani, Zhuoran Shen, Xiao Wang, Xiaohua Zhai, Thomas Kipf, Neil Houlsby

CoRR, 2022

Conditional Object-Centric Learning from Video.

Thomas Kipf, Gamaleldin Fathy Elsayed, Aravindh Mahendran, Austin Stone, Sara Sabour, Georg Heigold, Rico Jonschkowski, Alexey Dosovitskiy, Klaus Greff

Proceedings of the Tenth International Conference on Learning Representations, 2022

Simple Open-Vocabulary Object Detection.

Matthias Minderer, Alexey A. Gritsenko, Austin Stone, Maxim Neumann, Dirk Weissenborn, Alexey Dosovitskiy, Aravindh Mahendran, Anurag Arnab, Mostafa Dehghani, Zhuoran Shen, Xiao Wang, Xiaohua Zhai, Thomas Kipf, Neil Houlsby

Proceedings of the Computer Vision - ECCV 2022, 2022

Kubric: A scalable dataset generator.

Klaus Greff, Francois Belletti, Lucas Beyer, Carl Doersch, Yilun Du, Daniel Duckworth, David J. Fleet, Dan Gnanapragasam, Florian Golemo, Charles Herrmann, Thomas Kipf, Abhijit Kundu, Dmitry Lagun, Issam H. Laradji, Hsueh-Ti Derek Liu, Henning Meyer, Yishu Miao, Derek Nowrouzezahrai, A. Cengiz Öztireli, Etienne Pot, Noha Radwan, Daniel Rebain, Sara Sabour, Mehdi S. M. Sajjadi, Matan Sela, Vincent Sitzmann, Austin Stone, Deqing Sun, Suhani Vora, Ziyu Wang, Tianhao Wu, Kwang Moo Yi, Fangcheng Zhong, Andrea Tagliasacchi

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

The Distracting Control Suite - A Challenging Benchmark for Reinforcement Learning from Pixels.

Austin Stone, Oscar Ramirez, Kurt Konolige, Rico Jonschkowski

CoRR, 2021

SMURF: Self-Teaching Multi-Frame Unsupervised RAFT With Full-Image Warping.

Austin Stone, Daniel Maurer, Alper Ayvaci, Anelia Angelova, Rico Jonschkowski

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Coupling Shared and Tunable Negative Competition Against Winner-Take-All Resource Competition Via CRISPRi Moieties.

Austin Stone, Rong Zhang, Xiao-Jun Tian

Proceedings of the 2021 American Control Conference, 2021

2020

What Matters in Unsupervised Optical Flow.

Rico Jonschkowski, Austin Stone, Jonathan T. Barron, Ariel Gordon, Kurt Konolige, Anelia Angelova

Proceedings of the Computer Vision - ECCV 2020, 2020

Learning Object-conditioned Exploration using Distributed Soft Actor Critic.

Ayzaan Wahid, Austin Stone, Kevin Chen, Brian Ichter, Alexander Toshev

Proceedings of the 4th Conference on Robot Learning, 2020

2019

Towards Object Detection from Motion.

Rico Jonschkowski, Austin Stone

CoRR, 2019

2017

Teaching Compositionality to CNNs.

Austin Stone, Hua-Yan Wang, Michael Stark, Yi Liu, D. Scott Phoenix, Dileep George

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