| WaterGAN: Unsupervised Generative Network to Enable Real-time Color Correction of Monocular Underwater Images J Li, KA Skinner, RM Eustice, M Johnson-Roberson IEEE Robotics and Automation Letters, 8, 2017 | 851 | 2017 |
| Is pseudo-lidar needed for monocular 3d object detection? D Park, R Ambrus, V Guizilini, J Li, A Gaidon Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 363 | 2021 |
| Probabilistic 3D multi-modal, multi-object tracking for autonomous driving H Chiu, J Li, R Ambruş, J Bohg 2021 IEEE international conference on robotics and automation (ICRA), 14227 …, 2021 | 290 | 2021 |
| Semantically-guided representation learning for self-supervised monocular depth V Guizilini, R Hou, J Li, R Ambrus, A Gaidon arXiv preprint arXiv:2002.12319, 2020 | 278 | 2020 |
| Learning to track with object permanence P Tokmakov, J Li, W Burgard, A Gaidon Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 250 | 2021 |
| Spigan: Privileged adversarial learning from simulation KH Lee, G Ros, J Li, A Gaidon arXiv preprint arXiv:1810.03756, 2018 | 145 | 2018 |
| Learning to fuse things and stuff J Li, A Raventos, A Bhargava, T Tagawa, A Gaidon arXiv preprint arXiv:1812.01192, 2018 | 126 | 2018 |
| Pose-graph SLAM using forward-looking sonar J Li, M Kaess, RM Eustice, M Johnson-Roberson IEEE Robotics and Automation Letters 3 (3), 2330-2337, 2018 | 103 | 2018 |
| Real-time panoptic segmentation from dense detections R Hou, J Li, A Bhargava, A Raventos, V Guizilini, C Fang, J Lynch, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 89 | 2020 |
| Robust semi-supervised monocular depth estimation with reprojected distances V Guizilini, J Li, R Ambrus, S Pillai, A Gaidon Conference on robot learning, 503-512, 2020 | 69 | 2020 |
| Adversarial learning of photorealistic post-processing of simulation with privileged information KH Lee, G Ros, AD Gaidon, J Li US Patent 10,643,320, 2020 | 56 | 2020 |
| Standing between past and future: Spatio-temporal modeling for multi-camera 3d multi-object tracking Z Pang, J Li, P Tokmakov, D Chen, S Zagoruyko, YX Wang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 49 | 2023 |
| Geometric unsupervised domain adaptation for semantic segmentation V Guizilini, J Li, R Ambruș, A Gaidon Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 48 | 2021 |
| High-level visual features for underwater place recognition J Li, RM Eustice, M Johnson-Roberson IEEE International Conference on Robotics and Automation (ICRA), 2015 | 34 | 2015 |
| System and method for generating improved synthetic images GROS SANCHEZ, AD Gaidon, KH Lee, J Li US Patent 10,713,569, 2020 | 32 | 2020 |
| Gaussian processes semantic map representation MG Jadidi, L Gan, SA Parkison, J Li, RM Eustice arXiv preprint arXiv:1707.01532, 2017 | 26 | 2017 |
| Pillarflow: End-to-end birds-eye-view flow estimation for autonomous driving KH Lee, M Kliemann, A Gaidon, J Li, C Fang, S Pillai, W Burgard 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020 | 25 | 2020 |
| Object permanence emerges in a random walk along memory P Tokmakov, A Jabri, J Li, A Gaidon arXiv preprint arXiv:2204.01784, 2022 | 23 | 2022 |
| Two stream networks for self-supervised ego-motion estimation R Ambrus, V Guizilini, J Li, SPA Gaidon Conference on Robot Learning, 1052-1061, 2020 | 21 | 2020 |
| Utilizing high-dimensional features for real-time robotic applications: Reducing the curse of dimensionality for recursive bayesian estimation J Li, P Ozog, J Abernethy, RM Eustice, M Johnson-Roberson 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2016 | 21 | 2016 |
Adrien GaidonAdjunct Professor, StanfordПотвърден имейл адрес: stanford.edu