Peter Ondrúška
Peter Ondrúška
Head of Research, Lyft Level 5
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Ask me anything: Dynamic memory networks for natural language processing
A Kumar, O Irsoy, P Ondruska, M Iyyer, J Bradbury, I Gulrajani, V Zhong, ...
International conference on machine learning, 1378-1387, 2016
10652016
Maximum entropy deep inverse reinforcement learning
M Wulfmeier, P Ondruska, I Posner
arXiv preprint arXiv:1507.04888, 2015
1962015
Deep tracking: Seeing beyond seeing using recurrent neural networks
P Ondruska, I Posner
Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016
1492016
Mobilefusion: Real-time volumetric surface reconstruction and dense tracking on mobile phones
P Ondrúška, P Kohli, S Izadi
IEEE transactions on visualization and computer graphics 21 (11), 1251-1258, 2015
1092015
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
752017
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
732018
Deep tracking: Seeing beyond seeing using recurrent neural networks
P Ondrúška, I Posner
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence …, 2016
722016
Lyft level 5 av dataset 2019
R Kesten, M Usman, J Houston, T Pandya, K Nadhamuni, A Ferreira, ...
urlhttps://level5. lyft. com/dataset, 2019
572019
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
572016
Deep inverse reinforcement learning
M Wulfmeier, P Ondruska, I Posner
arXiv preprint arXiv:1507.04888, 2015
532015
Probabilistic attainability maps: Efficiently predicting driver-specific electric vehicle range
P Ondruska, I Posner
2014 IEEE Intelligent Vehicles Symposium Proceedings, 1169-1174, 2014
312014
Scheduled perception for energy-efficient path following
P Ondrúška, C Gurău, L Marchegiani, CH Tong, I Posner
2015 IEEE International Conference on Robotics and Automation (ICRA), 4799-4806, 2015
272015
Lyft level 5 av dataset 2019. urlhttps
R Kesten, M Usman, J Houston, T Pandya, K Nadhamuni, A Ferreira, ...
level5. lyft. com/dataset 2, 5, 2019
252019
The route not taken: Driver-centric estimation of electric vehicle range
P Ondruska, I Posner
Proceedings of the International Conference on Automated Planning and …, 2014
252014
One thousand and one hours: Self-driving motion prediction dataset
J Houston, G Zuidhof, L Bergamini, Y Ye, L Chen, A Jain, S Omari, ...
arXiv preprint arXiv:2006.14480, 2020
212020
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
202016
Collaborative Augmented Reality on Smartphones via Life-long City-scale Maps
L Platinsky, M Szabados, F Hlasek, R Hemsley, L Del Pero, A Pancik, ...
2020 IEEE International Symposium on Mixed and Augmented Reality (ISMAR …, 2020
22020
Method and system for creating a virtual 3D model
P Ondruska, L Platinsky
US Patent 10,460,511, 2019
22019
Enhanced vehicle tracking
P Ondruska, L Platinsky, SM Surendran
US Patent 10,668,921, 2020
12020
Visual vehicle tracking through noise and occlusions using crowd-sourced maps
MS Suraj, H Grimmett, L Platinský, P Ondrúška
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2018
12018
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