Rt-1: Robotics transformer for real-world control at scale A Brohan, N Brown, J Carbajal, Y Chebotar, J Dabis, C Finn, ... arXiv preprint arXiv:2212.06817, 2022 | 826 | 2022 |
Simple open-vocabulary object detection M Minderer, A Gritsenko, A Stone, M Neumann, D Weissenborn, ... European Conference on Computer Vision, 728-755, 2022 | 461 | 2022 |
What matters in unsupervised optical flow R Jonschkowski, A Stone, JT Barron, A Gordon, K Konolige, A Angelova Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 224 | 2020 |
Conditional object-centric learning from video T Kipf, GF Elsayed, A Mahendran, A Stone, S Sabour, G Heigold, ... arXiv preprint arXiv:2111.12594, 2021 | 206 | 2021 |
Kubric: A scalable dataset generator K Greff, F Belletti, L Beyer, C Doersch, Y Du, D Duckworth, DJ Fleet, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 202 | 2022 |
Open-vocabulary queryable scene representations for real world planning B Chen, F Xia, B Ichter, K Rao, K Gopalakrishnan, MS Ryoo, A Stone, ... 2023 IEEE International Conference on Robotics and Automation (ICRA), 11509 …, 2023 | 177 | 2023 |
Object tracking by an unmanned aerial vehicle using visual sensors S Dasgupta, H Martirosyan, H Koppula, A Kendall, A Stone, M Donahoe, ... US Patent 11,295,458, 2022 | 168 | 2022 |
Open-world object manipulation using pre-trained vision-language models A Stone, T Xiao, Y Lu, K Gopalakrishnan, KH Lee, Q Vuong, P Wohlhart, ... arXiv preprint arXiv:2303.00905, 2023 | 129 | 2023 |
Scaling robot learning with semantically imagined experience T Yu, T Xiao, A Stone, J Tompson, A Brohan, S Wang, J Singh, C Tan, ... arXiv preprint arXiv:2302.11550, 2023 | 113 | 2023 |
The Distracting Control Suite--A Challenging Benchmark for Reinforcement Learning from Pixels A Stone, O Ramirez, K Konolige, R Jonschkowski arXiv preprint arXiv:2101.02722, 2021 | 97 | 2021 |
Smurf: Self-teaching multi-frame unsupervised raft with full-image warping A Stone, D Maurer, A Ayvaci, A Angelova, R Jonschkowski Proceedings of the IEEE/CVF conference on Computer Vision and Pattern …, 2021 | 97 | 2021 |
Teaching compositionality to cnns A Stone, H Wang, M Stark, Y Liu, D Scott Phoenix, D George Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 77 | 2017 |
Simple open-vocabulary object detection with vision transformers. arxiv 2022 M Minderer, A Gritsenko, A Stone, M Neumann, D Weissenborn, ... arXiv preprint arXiv:2205.06230 2, 2022 | 48 | 2022 |
Token turing machines MS Ryoo, K Gopalakrishnan, K Kahatapitiya, T Xiao, K Rao, A Stone, Y Lu, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 21 | 2023 |
Learning object-conditioned exploration using distributed soft actor critic A Wahid, A Stone, K Chen, B Ichter, A Toshev Conference on Robot Learning, 1684-1695, 2021 | 19 | 2021 |
Self-supervised autoflow HP Huang, C Herrmann, J Hur, E Lu, K Sargent, A Stone, MH Yang, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 8 | 2023 |
TF-RAFT: A tensorflow implementation of raft D Sun, C Herrmann, V Jampani, M Krainin, F Cole, A Stone, ... ECCV Robust Vision Challenge Workshop 8, 2020 | 7 | 2020 |
Unsupervised training of optical flow estimation neural networks DR Maurer, AC Stone, A Ayvaci, A Angelova, R Jonschkowski US Patent App. 17/721,288, 2022 | 5 | 2022 |
Towards flexible perception with visual memory R Geirhos, P Jaini, A Stone, S Medapati, X Yi, G Toderici, A Ogale, ... arXiv preprint arXiv:2408.08172, 2024 | 2 | 2024 |
Towards object detection from motion R Jonschkowski, A Stone arXiv preprint arXiv:1909.12950, 2019 | 2 | 2019 |