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2020 – today
- 2022
[c14]Matt Vitelli, Yan Chang, Yawei Ye, Ana Ferreira, Maciej Wolczyk, Blazej Osinski, Moritz Niendorf, Hugo Grimmett, Qiangui Huang, Ashesh Jain, Peter Ondruska:
SafetyNet: Safe Planning for Real-World Self-Driving Vehicles Using Machine-Learned Policies. ICRA 2022: 897-904- 2021
- [c13]Oliver Scheel, Luca Bergamini, Maciej Wolczyk, Blazej Osinski, Peter Ondruska:
Urban Driver: Learning to Drive from Real-world Demonstrations Using Policy Gradients. CoRL 2021: 718-728 - [c12]Long Chen, Lukas Platinsky, Stefanie Speichert, Blazej Osinski, Oliver Scheel, Yawei Ye, Hugo Grimmett, Luca Del Pero, Peter Ondruska:
What data do we need for training an AV motion planner? ICRA 2021: 1066-1072 - [c11]Luca Bergamini, Yawei Ye, Oliver Scheel, Long Chen, Chih Hu, Luca Del Pero, Blazej Osinski, Hugo Grimmett, Peter Ondruska:
SimNet: Learning Reactive Self-driving Simulations from Real-world Observations. ICRA 2021: 5119-5125 - [i14]Luca Bergamini, Yawei Ye, Oliver Scheel, Long Chen, Chih Hu, Luca Del Pero, Blazej Osinski, Hugo Grimmett, Peter Ondruska:
SimNet: Learning Reactive Self-driving Simulations from Real-world Observations. CoRR abs/2105.12332 (2021) - [i13]Long Chen, Lukas Platinsky, Stefanie Speichert, Blazej Osinski, Oliver Scheel, Yawei Ye, Hugo Grimmett, Luca Del Pero, Peter Ondruska:
What data do we need for training an AV motion planner? CoRR abs/2105.12337 (2021) - [i12]Ashesh Jain, Luca Del Pero, Hugo Grimmett, Peter Ondruska:
Autonomy 2.0: Why is self-driving always 5 years away? CoRR abs/2107.08142 (2021) - [i11]Oliver Scheel, Luca Bergamini, Maciej Wolczyk, Blazej Osinski, Peter Ondruska:
Urban Driver: Learning to Drive from Real-world Demonstrations Using Policy Gradients. CoRR abs/2109.13333 (2021) - [i10]Matt Vitelli, Yan Chang, Yawei Ye, Maciej Wolczyk, Blazej Osinski, Moritz Niendorf, Hugo Grimmett, Qiangui Huang, Ashesh Jain, Peter Ondruska:
SafetyNet: Safe planning for real-world self-driving vehicles using machine-learned policies. CoRR abs/2109.13602 (2021) - [i9]Parth Kothari, Christian Perone, Luca Bergamini, Alexandre Alahi, Peter Ondruska:
DriverGym: Democratising Reinforcement Learning for Autonomous Driving. CoRR abs/2111.06889 (2021) - 2020
- [c10]John Houston, Guido Zuidhof, Luca Bergamini, Yawei Ye, Long Chen, Ashesh Jain, Sammy Omari, Vladimir Iglovikov, Peter Ondruska:
One Thousand and One Hours: Self-driving Motion Prediction Dataset. CoRL 2020: 409-418 - [c9]Lukas Platinsky, Michal Szabados, Filip Hlasek, Ross Hemsley, Luca Del Pero, Andrej Pancik, Bryan Baum, Hugo Grimmett, Peter Ondruska:
Collaborative Augmented Reality on Smartphones via Life-long City-scale Maps. ISMAR 2020: 533-541 - [i8]Giacomo Dabisias, Emanuele Ruffaldi, Hugo Grimmett, Peter Ondruska:
VALUE: Large Scale Voting-based Automatic Labelling for Urban Environments. CoRR abs/2006.03492 (2020) - [i7]John Houston, Guido Zuidhof, Luca Bergamini, Yawei Ye, Ashesh Jain, Sammy Omari, Vladimir Iglovikov, Peter Ondruska:
One Thousand and One Hours: Self-driving Motion Prediction Dataset. CoRR abs/2006.14480 (2020) - [i6]Lukas Platinsky, Michal Szabados, Filip Hlasek, Ross Hemsley, Luca Del Pero, Andrej Pancik, Bryan Baum, Hugo Grimmett, Peter Ondruska:
Collaborative Augmented Reality on Smartphones via Life-long City-scale Maps. CoRR abs/2011.05370 (2020)
2010 – 2019
- 2018
- [j3]Julie Dequaire, Peter Ondruska, Dushyant Rao, Dominic Zeng Wang, Ingmar Posner:
Deep tracking in the wild: End-to-end tracking using recurrent neural networks. Int. J. Robotics Res. 37(4-5): 492-512 (2018) - [c8]Giacomo Dabisias, Emanuele Ruffaldi, Hugo Grimmett, Peter Ondruska:
VALUE: Large Scale Voting-Based Automatic Labelling for Urban Environments. ICRA 2018: 1-6 - [c7]M. S. Suraj, Hugo Grimmett, Lukas Platinsky, Peter Ondruska:
Visual Vehicle Tracking Through Noise and Occlusions Using Crowd-Sourced Maps. IROS 2018: 4531-4538 - [c6]M. S. Suraj, Hugo Grimmett, Lukas Platinsky, Peter Ondruska:
Predicting trajectories of vehicles using large-scale motion priors. Intelligent Vehicles Symposium 2018: 1639-1644 - 2017
- [j2]Markus Wulfmeier, Dushyant Rao, Dominic Zeng Wang, Peter Ondruska, Ingmar Posner:
Large-scale cost function learning for path planning using deep inverse reinforcement learning. Int. J. Robotics Res. 36(10): 1073-1087 (2017) - 2016
- [c5]Peter Ondruska, Ingmar Posner:
Deep Tracking: Seeing Beyond Seeing Using Recurrent Neural Networks. AAAI 2016: 3361-3368 - [c4]Ankit Kumar, Ozan Irsoy, Peter Ondruska, Mohit Iyyer, James Bradbury, Ishaan Gulrajani, Victor Zhong, Romain Paulus, Richard Socher:
Ask Me Anything: Dynamic Memory Networks for Natural Language Processing. ICML 2016: 1378-1387 - [i5]Peter Ondruska, Ingmar Posner:
Deep Tracking: Seeing Beyond Seeing Using Recurrent Neural Networks. CoRR abs/1602.00991 (2016) - [i4]Peter Ondruska, Julie Dequaire, Dominic Zeng Wang, Ingmar Posner:
End-to-End Tracking and Semantic Segmentation Using Recurrent Neural Networks. CoRR abs/1604.05091 (2016) - [i3]Julie Dequaire, Dushyant Rao, Peter Ondruska, Dominic Zeng Wang, Ingmar Posner:
Deep Tracking on the Move: Learning to Track the World from a Moving Vehicle using Recurrent Neural Networks. CoRR abs/1609.09365 (2016) - 2015
- [j1]Peter Ondruska, Pushmeet Kohli, Shahram Izadi:
MobileFusion: Real-Time Volumetric Surface Reconstruction and Dense Tracking on Mobile Phones. IEEE Trans. Vis. Comput. Graph. 21(11): 1251-1258 (2015) - [c3]Peter Ondruska, Corina Gurau, Letizia Marchegiani
, Chi Hay Tong, Ingmar Posner:
Scheduled perception for energy-efficient path following. ICRA 2015: 4799-4806 - [i2]Ankit Kumar, Ozan Irsoy, Jonathan Su, James Bradbury, Robert English, Brian Pierce, Peter Ondruska, Ishaan Gulrajani, Richard Socher:
Ask Me Anything: Dynamic Memory Networks for Natural Language Processing. CoRR abs/1506.07285 (2015) - [i1]Markus Wulfmeier, Peter Ondruska, Ingmar Posner:
Deep Inverse Reinforcement Learning. CoRR abs/1507.04888 (2015) - 2014
- [c2]Peter Ondruska, Ingmar Posner:
The Route Not Taken: Driver-Centric Estimation of Electric Vehicle Range. ICAPS 2014 - [c1]Peter Ondruska, Ingmar Posner:
Probabilistic attainability maps: Efficiently predicting driver-specific electric vehicle range. Intelligent Vehicles Symposium 2014: 1169-1174
Coauthor Index
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