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End-to-end driving systems have recently made rapid progress, in particular on CARLA.
ALVINN: an autonomous land vehicle in a neural network
Dean Pomerleau · 1988
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The unscented kalman filter for nonlinear estimation
Eric A Wan and Rudolph Van Der Merwe · 2000
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Sigma-point Kalman filters for probabilistic inference in dynamic state-space models
Rudolph Van Der Merwe · 2004
Earlier work this paper cites.
A reduction of imitation learning and structured prediction to no-regret online learning
Stéphane Ross, Geoffrey J. Gordon, and Drew Bagnell · 2011
Earlier work this paper cites.
Laszip: lossless compression of lidar data
Martin Isenburg · 2013
Earlier work this paper cites.
Learning phrase representations using RNN encoder-decoder for statistical machine translation
Kyunghyun Cho, Bart van Merrienboer, Çaglar Gülçehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio · 2014
Earlier work this paper cites.
Layer normalization
Lei Jimmy Ba, Jamie Ryan Kiros, and Geoffrey E. Hinton · 2016
Earlier work this paper cites.
End to end learning for self-driving cars
Mariusz Bojarski, Davide Del Testa, Daniel Dworakowski, Bernhard Firner, Beat Flepp, Prasoon Goyal, Lawrence D. Jackel, Mathew Monfort, Urs Muller, Jiakai Zhang, Xin Zhang, Jake Zhao, and Karol Zieba · 2016
Earlier work this paper cites.
Gaussian error linear units (gelus)
Dan Hendrycks and Kevin Gimpel · 2016
Earlier work this paper cites.
CARLA: An open urban driving simulator
Alexey Dosovitskiy, German Ros, Felipe Codevilla, Antonio Lopez, and Vladlen Koltun · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
End-to-end driving via conditional imitation learning
Felipe Codevilla, Matthias Miiller, Antonio López, Vladlen Koltun, and Alexey Dosovitskiy · 2018
Earlier work this paper cites.
On the convergence of adam and beyond
Sashank J. Reddi, Satyen Kale, and Sanjiv Kumar · 2018
Earlier work this paper cites.
Conditional affordance learning for driving in urban environments
Axel Sauer, Nikolay Savinov, and Andreas Geiger · 2018
Earlier work this paper cites.
Chauffeurnet: Learning to drive by imitating the best and synthesizing the worst
Mayank Bansal, Alex Krizhevsky, and Abhijit S. Ogale · 2019
Earlier work this paper cites.
Learning by cheating
Dian Chen, Brady Zhou, Vladlen Koltun, and Philipp Krähenbühl · 2019
Cited alongside, same era.
Exploring the limitations of behavior cloning for autonomous driving
Felipe Codevilla, Eder Santana, Antonio M. López, and Adrien Gaidon · 2019
Cited alongside, same era.
Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2019
Cited alongside, same era.
https://leaderboard.carla.org/ , 2020
Carla autonomous driving leaderboard · 2020
Cited alongside, same era.
Label efficient visual abstractions for autonomous driving
Aseem Behl, Kashyap Chitta, Aditya Prakash, Eshed Ohn-Bar, and Andreas Geiger · 2020
Cited alongside, same era.
Shortcut learning in deep neural networks
Robert Geirhos, Jörn-Henrik Jacobsen, Claudio Michaelis, Richard S. Zemel, Wieland Brendel, Matthias Bethge, and Felix A. Wichmann · 2020
Cited alongside, same era.
Neat: Neural attention fields for end-to-end autonomous driving
Kashyap Chitta, Aditya Prakash, and Andreas Geiger · 2021
Later among the works it cites.
Expert drivers for autonomous driving
Bernhard Jaeger · 2021
Later among the works it cites.
Multi-modal fusion transformer for end-to-end autonomous driving
Aditya Prakash, Kashyap Chitta, and Andreas Geiger · 2021
Later among the works it cites.
End-to-end urban driving by imitating a reinforcement learning coach
Zhejun Zhang, Alexander Liniger, Dengxin Dai, Fisher Yu, and Luc Van Gool · 2021
Later among the works it cites.
Vista 2.0: An open, data-driven simulator for multimodal sensing and policy learning for autonomous vehicles
Alexander Amini, Tsun-Hsuan Wang, Igor Gilitschenski, Wilko Schwarting, Zhijian Liu, Song Han, Sertac Karaman, and Daniela Rus · 2022
Later among the works it cites.
Learning from all vehicles
Dian Chen and Philipp Krähenbühl · 2022
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Learning situational driving
Eshed Ohn-Bar, Aditya Prakash, Aseem Behl, Kashyap Chitta, and Andreas Geiger · 2020
Cited alongside, same era.
Exploring data aggregation in policy learning for vision-based urban autonomous driving
Aditya Prakash, Aseem Behl, Eshed Ohn-Bar, Kashyap Chitta, and Andreas Geiger · 2020
Cited alongside, same era.
Designing network design spaces
Ilija Radosavovic, Raj Prateek Kosaraju, Ross B. Girshick, Kaiming He, and Piotr Dollár · 2020
Cited alongside, same era.
Kalman and bayesian filters in python
Labbe Roger · 2020
Cited alongside, same era.
End-to-end model-free reinforcement learning for urban driving using implicit affordances
Marin Toromanoff, Emilie Wirbel, and Fabien Moutarde · 2020
Cited alongside, same era.
Fighting copycat agents in behavioral cloning from observation histories
Chuan Wen, Jierui Lin, Trevor Darrell, Dinesh Jayaraman, and Yang Gao · 2020
Cited alongside, same era.
Later among the works it cites.
Transfuser: Imitation with transformer-based sensor fusion for autonomous driving
Kashyap Chitta, Aditya Prakash, Bernhard Jaeger, Zehao Yu, Katrin Renz, and Andreas Geiger · 2022
Later among the works it cites.
Model-based imitation learning for urban driving
Anthony Hu, Gianluca Corrado, Nicolas Griffiths, Zak Murez, Corina Gurau, Hudson Yeo, Alex Kendall, Roberto Cipolla, and Jamie Shotton · 2022
Later among the works it cites.
Plant: Explainable planning transformers via object-level representations
Katrin Renz, Kashyap Chitta, Otniel-Bogdan Mercea, Almut Sophia Koepke, Zeynep Akata, and Andreas Geiger · 2022
Later among the works it cites.
Safety-enhanced autonomous driving using interpretable sensor fusion transformer
Hao Shao, Letian Wang, RuoBing Chen, Hongsheng Li, and Yu Liu · 2022
Later among the works it cites.
Trajectory-guided control prediction for end-to-end autonomous driving: A simple yet strong baseline
Peng Wu, Xiaosong Jia, Li Chen, Junchi Yan, Hongyang Li, and Yu Qiao · 2022
Later among the works it cites.
Think twice before driving: Towards scalable decoders for end-to-end autonomous driving
Xiaosong Jia, Penghao Wu, Li Chen, Jiangwei Xie, Conghui He, Junchi Yan, and Hongyang Li · 2023
Closest in time.
Reasonnet: End-to-end driving with temporal and global reasoning
Hao Shao, Letian Wang, Ruobing Chen, Steven L. Waslander, Hongsheng Li, and Yu Liu · 2023
Closest in time.
Coaching a teachable student
Jimuyang Zhang, Zanming Huang, and Eshed Ohn-Bar · 2023
Closest in time.