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Conference and Workshop Papers
- 2023
[c14]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:
Open-World Object Manipulation using Pre-Trained Vision-Language Models. CoRL 2023: 3397-3417- [c13]Hsin-Ping Huang, Charles Herrmann, Junhwa Hur, Erika Lu, Kyle Sargent, Austin Stone, Ming-Hsuan Yang, Deqing Sun:
Self-supervised AutoFlow. CVPR 2023: 11412-11421 - [c12]Michael S. Ryoo, Keerthana Gopalakrishnan, Kumara Kahatapitiya, Ted Xiao, Kanishka Rao, Austin Stone, Yao Lu, Julian Ibarz, Anurag Arnab:
Token Turing Machines. CVPR 2023: 19070-19081 - [c11]Boyuan Chen, Fei Xia, Brian Ichter, Kanishka Rao, Keerthana Gopalakrishnan, Michael S. Ryoo, Austin Stone, Daniel Kappler:
Open-vocabulary Queryable Scene Representations for Real World Planning. ICRA 2023: 11509-11522 - [c10]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:
RT-1: Robotics Transformer for Real-World Control at Scale. Robotics: Science and Systems 2023 - [c9]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:
Scaling Robot Learning with Semantically Imagined Experience. Robotics: Science and Systems 2023 - 2022
- [c8]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:
Kubric: A scalable dataset generator. CVPR 2022: 3739-3751 - [c7]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:
Simple Open-Vocabulary Object Detection. ECCV (10) 2022: 728-755 - [c6]Thomas Kipf, Gamaleldin Fathy Elsayed, Aravindh Mahendran, Austin Stone, Sara Sabour, Georg Heigold, Rico Jonschkowski, Alexey Dosovitskiy, Klaus Greff:
Conditional Object-Centric Learning from Video. ICLR 2022 - 2021
- [c5]Austin Stone, Rong Zhang, Xiao-Jun Tian
:
Coupling Shared and Tunable Negative Competition Against Winner-Take-All Resource Competition Via CRISPRi Moieties. ACC 2021: 1882 - [c4]Austin Stone, Daniel Maurer, Alper Ayvaci, Anelia Angelova, Rico Jonschkowski:
SMURF: Self-Teaching Multi-Frame Unsupervised RAFT With Full-Image Warping. CVPR 2021: 3887-3896 - 2020
- [c3]Ayzaan Wahid, Austin Stone, Kevin Chen, Brian Ichter, Alexander Toshev:
Learning Object-conditioned Exploration using Distributed Soft Actor Critic. CoRL 2020: 1684-1695 - [c2]Rico Jonschkowski, Austin Stone, Jonathan T. Barron, Ariel Gordon, Kurt Konolige, Anelia Angelova:
What Matters in Unsupervised Optical Flow. ECCV (2) 2020: 557-572 - 2017
- [c1]Austin Stone, Hua-Yan Wang, Michael Stark, Yi Liu, D. Scott Phoenix, Dileep George:
Teaching Compositionality to CNNs. CVPR 2017: 732-741
Informal and Other Publications
- 2024
- [i16]Robert Geirhos, Priyank Jaini, Austin Stone, Sourabh Medapati, Xi Yi, George Toderici, Abhijit Ogale, Jonathon Shlens:
Towards flexible perception with visual memory. CoRR abs/2408.08172 (2024) - 2023
- [i15]Tianhe Yu, Ted Xiao, Austin Stone, Jonathan Tompson, Anthony Brohan, Su Wang, Jaspiar Singh, Clayton Tan, Dee M, Jodilyn Peralta, Brian Ichter, Karol Hausman, Fei Xia:
Scaling Robot Learning with Semantically Imagined Experience. CoRR abs/2302.11550 (2023) - [i14]Austin Stone, Ted Xiao, Yao Lu, Keerthana Gopalakrishnan, Kuang-Huei Lee, Quan Vuong, Paul Wohlhart, Brianna Zitkovich, Fei Xia, Chelsea Finn, Karol Hausman:
Open-World Object Manipulation using Pre-trained Vision-Language Models. CoRR abs/2303.00905 (2023) - 2022
- [i13]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, 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:
Kubric: A scalable dataset generator. CoRR abs/2203.03570 (2022) - [i12]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:
Simple Open-Vocabulary Object Detection with Vision Transformers. CoRR abs/2205.06230 (2022) - [i11]Boyuan Chen, Fei Xia, Brian Ichter, Kanishka Rao, Keerthana Gopalakrishnan, Michael S. Ryoo, Austin Stone, Daniel Kappler:
Open-vocabulary Queryable Scene Representations for Real World Planning. CoRR abs/2209.09874 (2022) - [i10]Michael S. Ryoo, Keerthana Gopalakrishnan, Kumara Kahatapitiya, Ted Xiao, Kanishka Rao, Austin Stone, Yao Lu, Julian Ibarz, Anurag Arnab:
Token Turing Machines. CoRR abs/2211.09119 (2022) - [i9]Hsin-Ping Huang, Charles Herrmann, Junhwa Hur, Erika Lu, Kyle Sargent, Austin Stone, Ming-Hsuan Yang, Deqing Sun:
Self-supervised AutoFlow. CoRR abs/2212.01762 (2022) - [i8]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 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:
RT-1: Robotics Transformer for Real-World Control at Scale. CoRR abs/2212.06817 (2022) - 2021
- [i7]Austin Stone, Oscar Ramirez, Kurt Konolige, Rico Jonschkowski:
The Distracting Control Suite - A Challenging Benchmark for Reinforcement Learning from Pixels. CoRR abs/2101.02722 (2021) - [i6]Austin Stone, Daniel Maurer, Alper Ayvaci, Anelia Angelova, Rico Jonschkowski:
SMURF: Self-Teaching Multi-Frame Unsupervised RAFT with Full-Image Warping. CoRR abs/2105.07014 (2021) - [i5]Thomas Kipf, Gamaleldin F. Elsayed, Aravindh Mahendran, Austin Stone, Sara Sabour, Georg Heigold, Rico Jonschkowski, Alexey Dosovitskiy, Klaus Greff:
Conditional Object-Centric Learning from Video. CoRR abs/2111.12594 (2021) - 2020
- [i4]Rico Jonschkowski, Austin Stone, Jonathan T. Barron, Ariel Gordon, Kurt Konolige, Anelia Angelova:
What Matters in Unsupervised Optical Flow. CoRR abs/2006.04902 (2020) - [i3]Ayzaan Wahid, Austin Stone, Kevin Chen, Brian Ichter, Alexander Toshev:
Learning Object-conditioned Exploration using Distributed Soft Actor Critic. CoRR abs/2007.14545 (2020) - 2019
- [i2]Rico Jonschkowski, Austin Stone:
Towards Object Detection from Motion. CoRR abs/1909.12950 (2019) - 2017
- [i1]Austin Stone, Hua-Yan Wang, Michael Stark, Yi Liu, D. Scott Phoenix, Dileep George:
Teaching Compositionality to CNNs. CoRR abs/1706.04313 (2017)
Coauthor Index
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