| Densefusion: 6d object pose estimation by iterative dense fusion C Wang, D Xu, Y Zhu, R Martín-Martín, C Lu, L Fei-Fei, S Savarese IEEE/CVF Conference on Computer Vision and Pattern Recognition, 3343-3352, 2019 | 1211 | 2019 |
| Social-bigat: Multimodal trajectory forecasting using bicycle-gan and graph attention networks V Kosaraju, A Sadeghian, R Martín-Martín, I Reid, SH Rezatofighi, ... Advances in Neural Information Processing Systems 2019 (NeurIPS), 2019 | 778 | 2019 |
| Open x-embodiment: Robotic learning datasets and rt-x models A O'Neill, A Rehman, A Gupta, A Maddukuri, A Gupta, A Padalkar, A Lee, ... arXiv preprint arXiv:2310.08864, 2023 | 469* | 2023 |
| robosuite: A modular simulation framework and benchmark for robot learning Y Zhu, J Wong, A Mandlekar, R Martín-Martín, A Joshi, S Nasiriany, Y Zhu arXiv preprint arXiv:2009.12293, 2020 | 445 | 2020 |
| What matters in learning from offline human demonstrations for robot manipulation A Mandlekar, D Xu, J Wong, S Nasiriany, C Wang, R Kulkarni, L Fei-Fei, ... arXiv preprint arXiv:2108.03298, 2021 | 425 | 2021 |
| Lessons from the amazon picking challenge: Four aspects of building robotic systems. C Eppner, S Höfer, R Jonschkowski, R Martín-Martín, A Sieverling, V Wall, ... Robotics: science and systems, 4831-4835, 2016 | 267 | 2016 |
| Interactive gibson benchmark: A benchmark for interactive navigation in cluttered environments F Xia, WB Shen, C Li, P Kasimbeg, ME Tchapmi, A Toshev, ... IEEE Robotics and Automation Letters 5 (2), 713-720, 2020 | 240 | 2020 |
| Ulip: Learning a unified representation of language, images, and point clouds for 3d understanding L Xue, M Gao, C Xing, R Martín-Martín, J Wu, C Xiong, R Xu, JC Niebles, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 237 | 2023 |
| iGibson 2.0: Object-Centric Simulation for Robot Learning of Everyday Household Tasks C Li, F Xia, R Martín-Martín, M Lingelbach, S Srivastava, B Shen, K Vainio, ... Conference on Robot Learning, 455--465, 2022 | 222 | 2022 |
| Variable impedance control in end-effector space: An action space for reinforcement learning in contact-rich tasks R Martín-Martín, MA Lee, R Gardner, S Savarese, J Bohg, A Garg IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS …, 2019 | 220 | 2019 |
| 6-pack: Category-level 6d pose tracker with anchor-based keypoints C Wang, R Martín-Martín, D Xu, J Lv, C Lu, L Fei-Fei, S Savarese, Y Zhu 2020 IEEE International Conference on Robotics and Automation (ICRA), 10059 …, 2020 | 181 | 2020 |
| Behavior-1k: A benchmark for embodied ai with 1,000 everyday activities and realistic simulation C Li, R Zhang, J Wong, C Gokmen, S Srivastava, R Martín-Martín, C Wang, ... Conference on Robot Learning, 80-93, 2023 | 176 | 2023 |
| iGibson 1.0, a Simulation Environment for Interactive Tasks in Large Realistic Scenes B Shen, F Xia, C Li, R Martín-Martín, L Fan, G Wang, S Buch, C D'Arpino, ... IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021 | 174 | 2021 |
| Behavior: Benchmark for everyday household activities in virtual, interactive, and ecological environments S Srivastava, C Li, M Lingelbach, R Martín-Martín, F Xia, KE Vainio, Z Lian, ... Conference on robot learning, 477-490, 2022 | 156 | 2022 |
| Jrdb: A dataset and benchmark of egocentric robot visual perception of humans in built environments R Martin-Martin, M Patel, H Rezatofighi, A Shenoi, JY Gwak, E Frankel, ... IEEE transactions on pattern analysis and machine intelligence 45 (6), 6748-6765, 2021 | 153* | 2021 |
| Learning to generalize across long-horizon tasks from human demonstrations A Mandlekar, D Xu, R Martín-Martín, S Savarese, L Fei-Fei Robotics: Science and Systems (RSS), 2020 | 147 | 2020 |
| ReLMoGen: Leveraging motion generation in reinforcement learning for mobile manipulation F Xia, C Li, R Martín-Martín, O Litany, A Toshev, S Savarese 2021 International Conference on Robotics and Automation (ICRA), 2021 | 139* | 2021 |
| Mechanical search: Multi-step retrieval of a target object occluded by clutter M Danielczuk, A Kurenkov, A Balakrishna, M Matl, D Wang, ... 2019 International Conference on Robotics and Automation (ICRA), 1614-1621, 2019 | 136 | 2019 |
| Maskvit: Masked visual pre-training for video prediction A Gupta, S Tian, Y Zhang, J Wu, R Martín-Martín, L Fei-Fei arXiv preprint arXiv:2206.11894, 2022 | 129 | 2022 |
| Greedy hierarchical variational autoencoders for large-scale video prediction B Wu, S Nair, R Martin-Martin, L Fei-Fei, C Finn Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 125 | 2021 |
Silvio SavareseAssociate Professor of Computer Science at Stanford UniversityVerified email at stanford.edu
