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Dominic Zeng Wang
Dominic Zeng Wang
Woven by Toyota
Verified email at woven.toyota
Title
Cited by
Cited by
Year
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
6592017
Voting for Voting in Online Point Cloud Object Detection.
DZ Wang, I Posner
Robotics: Science and Systems 1 (3), 2015
4492015
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
1812017
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
1402012
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
1382016
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
1192018
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
1052015
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
852016
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
302016
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
132016
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