| Vote3deep: Fast object detection in 3d point clouds using efficient convolutional neural networks M Engelcke, D Rao, DZ Wang, CH Tong, I Posner 2017 IEEE International Conference on Robotics and Automation (ICRA), 1355-1361, 2017 | 689 | 2017 |
| Voting for Voting in Online Point Cloud Object Detection. DZ Wang, I Posner Robotics: Science and Systems 1 (3), 2015 | 462 | 2015 |
| Large-scale cost function learning for path planning using deep inverse reinforcement learning M Wulfmeier, D Rao, DZ Wang, P Ondruska, I Posner The International Journal of Robotics Research 36 (10), 1073-1087, 2017 | 192 | 2017 |
| What could move? finding cars, pedestrians and bicyclists in 3d laser data DZ Wang, I Posner, P Newman 2012 IEEE International Conference on Robotics and Automation (ICRA), 4038-4044, 2012 | 144 | 2012 |
| Watch this: Scalable cost-function learning for path planning in urban environments M Wulfmeier, DZ Wang, I Posner 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2016 | 141 | 2016 |
| Deep tracking in the wild: End-to-end tracking using recurrent neural networks J Dequaire, P Ondrúška, D Rao, D Wang, I Posner The International Journal of Robotics Research 37 (4-5), 492-512, 2018 | 129 | 2018 |
| Model-free detection and tracking of dynamic objects with 2D lidar DZ Wang, I Posner, P Newman The International Journal of Robotics Research 34 (7), 1039-1063, 2015 | 104 | 2015 |
| End-to-end tracking and semantic segmentation using recurrent neural networks P Ondruska, J Dequaire, DZ Wang, I Posner arXiv preprint arXiv:1604.05091, 2016 | 86 | 2016 |
| Deep tracking on the move: Learning to track the world from a moving vehicle using recurrent neural networks J Dequaire, D Rao, P Ondruska, D Wang, I Posner arXiv preprint arXiv:1609.09365, 2016 | 32 | 2016 |
| A new approach to model-free tracking with 2D lidar DZ Wang, I Posner, P Newman Robotics Research: The 16th International Symposium ISRR, 557-573, 2016 | 13 | 2016 |
