| 3d bounding box estimation using deep learning and geometry A Mousavian, D Anguelov, J Flynn, J Kosecka Proceedings of the IEEE conference on Computer Vision and Pattern …, 2017 | 1320 | 2017 |
| Progprompt: Generating situated robot task plans using large language models I Singh, V Blukis, A Mousavian, A Goyal, D Xu, J Tremblay, D Fox, ... 2023 IEEE International Conference on Robotics and Automation (ICRA), 11523 …, 2023 | 728 | 2023 |
| 6-dof graspnet: Variational grasp generation for object manipulation A Mousavian, C Eppner, D Fox Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 677 | 2019 |
| Contact-graspnet: Efficient 6-dof grasp generation in cluttered scenes M Sundermeyer, A Mousavian, R Triebel, D Fox 2021 IEEE International Conference on Robotics and Automation (ICRA), 13438 …, 2021 | 382 | 2021 |
| Synthesizing training data for object detection in indoor scenes G Georgakis, A Mousavian, AC Berg, J Kosecka arXiv preprint arXiv:1702.07836, 2017 | 275 | 2017 |
| 6-dof grasping for target-driven object manipulation in clutter A Murali, A Mousavian, C Eppner, C Paxton, D Fox 2020 IEEE International Conference on Robotics and Automation (ICRA), 6232-6238, 2020 | 252 | 2020 |
| Visual representations for semantic target driven navigation A Mousavian, A Toshev, M Fišer, J Košecká, A Wahid, J Davidson 2019 International Conference on Robotics and Automation (ICRA), 8846-8852, 2019 | 249 | 2019 |
| PoseRBPF: A Rao–Blackwellized particle filter for 6-D object pose tracking X Deng, A Mousavian, Y Xiang, F Xia, T Bretl, D Fox IEEE Transactions on Robotics 37 (5), 1328-1342, 2021 | 240 | 2021 |
| Self-supervised 6d object pose estimation for robot manipulation X Deng, Y Xiang, A Mousavian, C Eppner, T Bretl, D Fox 2020 IEEE International Conference on Robotics and Automation (ICRA), 3665-3671, 2020 | 220 | 2020 |
| Acronym: A large-scale grasp dataset based on simulation C Eppner, A Mousavian, D Fox 2021 IEEE International Conference on Robotics and Automation (ICRA), 6222-6227, 2021 | 210 | 2021 |
| Joint semantic segmentation and depth estimation with deep convolutional networks A Mousavian, H Pirsiavash, J Košecká 2016 Fourth International Conference on 3D Vision (3DV), 611-619, 2016 | 172 | 2016 |
| Deep learning approaches to grasp synthesis: A review R Newbury, M Gu, L Chumbley, A Mousavian, C Eppner, J Leitner, J Bohg, ... IEEE Transactions on Robotics 39 (5), 3994-4015, 2023 | 161 | 2023 |
| Unseen object instance segmentation for robotic environments C Xie, Y Xiang, A Mousavian, D Fox IEEE Transactions on Robotics 37 (5), 1343-1359, 2021 | 155 | 2021 |
| Latentfusion: End-to-end differentiable reconstruction and rendering for unseen object pose estimation K Park, A Mousavian, Y Xiang, D Fox Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 153 | 2020 |
| Learning rgb-d feature embeddings for unseen object instance segmentation Y Xiang, C Xie, A Mousavian, D Fox Conference on Robot Learning, 461-470, 2021 | 137 | 2021 |
| Megapose: 6d pose estimation of novel objects via render & compare Y Labbé, L Manuelli, A Mousavian, S Tyree, S Birchfield, J Tremblay, ... arXiv preprint arXiv:2212.06870, 2022 | 131 | 2022 |
| Storm: An integrated framework for fast joint-space model-predictive control for reactive manipulation M Bhardwaj, B Sundaralingam, A Mousavian, ND Ratliff, D Fox, F Ramos, ... Conference on Robot Learning, 750-759, 2022 | 129 | 2022 |
| The best of both modes: Separately leveraging rgb and depth for unseen object instance segmentation C Xie, Y Xiang, A Mousavian, D Fox Conference on robot learning, 1369-1378, 2020 | 110 | 2020 |
| Multiview rgb-d dataset for object instance detection G Georgakis, MA Reza, A Mousavian, PH Le, J Košecká 2016 Fourth international conference on 3D vision (3DV), 426-434, 2016 | 102 | 2016 |
| Object rearrangement using learned implicit collision functions M Danielczuk, A Mousavian, C Eppner, D Fox 2021 IEEE International Conference on Robotics and Automation (ICRA), 6010-6017, 2021 | 93 | 2021 |
Dieter FoxUniversity of Washington and NVIDIADirección de correo verificada de cs.washington.edu
