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An accurate model of the environment and the dynamic agents acting in it offers great potential for improving motion planning.
ALVINN: An autonomous land vehicle in a neural network
D. A. Pomerleau · 1988
Earlier work this paper cites.
Unsupervised learning
H. B. Barlow · 1989
Earlier work this paper cites.
Multiple paired forward and inverse models for motor control
D. M. Wolpert and M. Kawato · 1998
Earlier work this paper cites.
Odin: Team VictorTango’s Entry in the DARPA Urban Challenge
A. Bacha, C. Bauman, R. Faruque, M. Fleming, C. Terwelp, C. Reinholtz, D. Hong, A. Wicks, T. Alberi, D. Anderson, et al · 2008
Earlier work this paper cites.
Practical search techniques in path planning for autonomous driving
D. Dolgov, S. Thrun, M. Montemerlo, and J. Diebel · 2008
Earlier work this paper cites.
A perception-driven autonomous urban vehicle
J. Leonard, J. How, S. Teller, M. Berger, S. Campbell, G. Fiore, L. Fletcher, E. Frazzoli, A. Huang, S. Karaman, et al · 2008
Earlier work this paper cites.
A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning
S. Ross, G. Gordon, and D. Bagnell · 2011
Earlier work this paper cites.
Probabilistic model-based imitation learning
P. Englert, A. Paraschos, M. P. Deisenroth, and J. Peters · 2013
Earlier work this paper cites.
Auto-encoding variational bayes
D. P. Kingma and M. Welling · 2014
Earlier work this paper cites.
Computational cognitive models of spatial memory in navigation space: A review
T. Madl, K. Chen, D. Montaldi, and R. Trappl · 2015
Earlier work this paper cites.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Earlier work this paper cites.
CARLA: An Open Urban Driving Simulator
A. Dosovitskiy, G. Ros, F. Codevilla, A. Lopez, and V. Koltun · 2017
Earlier work this paper cites.
DESIRE: distant future prediction in dynamic scenes with interacting agents
N. Lee, W. Choi, P. Vernaza, C. B. Choy, P. H. S. Torr, and M. K. Chandraker · 2017
Earlier work this paper cites.
Rethinking Atrous Convolution for Semantic Image Segmentation
L.-C. Chen, G. Papandreou, F. Schroff, and H. Adam · 2017
Earlier work this paper cites.
The cognitive map in humans: spatial navigation and beyond
R. A. Epstein, E. Z. Patai, J. B. Julian, and H. J. Spiers · 2017
Earlier work this paper cites.
Recurrent world models facilitate policy evolution
D. Ha and J. Schmidhuber · 2018
Earlier work this paper cites.
End-to-end driving via conditional imitation learning
F. Codevilla, M. Müller, A. López, V. Koltun, and A. Dosovitskiy · 2018
Earlier work this paper cites.
Stochastic variational video prediction
M. Babaeizadeh, C. Finn, D. Erhan, R. H. Campbell, and S. Levine · 2018
Earlier work this paper cites.
Stochastic Video Generation with a Learned Prior
E. Denton and R. Fergus · 2018
Earlier work this paper cites.
Navigation in real-world environments: New opportunities afforded by advances in mobile brain imaging
J. L. Park, P. A. Dudchenko, and D. I. Donaldson · 2018
Cited alongside, same era.
Learning Latent Dynamics for Planning from Pixels
D. Hafner, T. Lillicrap, I. Fischer, R. Villegas, D. Ha, H. Lee, and J. Davidson · 2019
Cited alongside, same era.
Exploring the Limitations of Behavior Cloning for Autonomous Driving
F. Codevilla, E. Santana, A. M. López, and A. Gaidon · 2019
Cited alongside, same era.
ChauffeurNet: Learning to drive by imitating the best and synthesizing the worst
M. Bansal, A. Krizhevsky, and A. Ogale · 2019
Cited alongside, same era.
PRECOG: prediction conditioned on goals in visual multi-agent settings
N. Rhinehart, R. McAllister, K. M. Kitani, and S. Levine · 2019
Cited alongside, same era.
Digging into self-supervised monocular depth prediction
Deep imitative models for flexible inference, planning, and control
N. Rhinehart, R. McAllister, and S. Levine · 2020
Later among the works it cites.
End-to-end model-free reinforcement learning for urban driving using implicit affordances
M. Toromanoff, E. Wirbel, and F. Moutarde · 2020
Later among the works it cites.
Learning by cheating
D. Chen, B. Zhou, V. Koltun, and P. Krähenbühl · 2020
Later among the works it cites.
Panoptic-deeplab: A simple, strong, and fast baseline for bottom-up panoptic segmentation
B. Cheng, M. D. Collins, Y. Zhu, T. Liu, T. S. Huang, H. Adam, and L. Chen · 2020
Later among the works it cites.
Mastering atari with discrete world models
D. Hafner, T. Lillicrap, M. Norouzi, and J. Ba · 2021
Later among the works it cites.
Learning to drive from a world on rails
D. Chen, V. Koltun, and P. Krähenbühl · 2021
Later among the works it cites.
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C. Godard, O. Mac Aodha, M. Firman, and G. J. Brostow · 2019
Cited alongside, same era.
A style-based generator architecture for generative adversarial networks
T. Karras, S. Laine, and T. Aila · 2019
Cited alongside, same era.
Decoupled Weight Decay Regularization
I. Loshchilov and F. Hutter · 2019
Cited alongside, same era.
CARLA Autonomous Driving Leaderboard
CARLA Team · 2019
Cited alongside, same era.
Model-Predictive Policy Learning with Uncertainty Regularization for Driving in Dense Traffic
M. Henaff, A. Canziani, and Y. LeCun · 2019
Cited alongside, same era.
Urban Driving with Conditional Imitation Learning
J. Hawke, R. Shen, C. Gurau, S. Sharma, D. Reda, N. Nikolov, P. Mazur, S. Micklethwaite, N. Griffiths, A. Shah, et al · 2020
Cited alongside, same era.
Lift, splat, shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3d
J. Philion and S. Fidler · 2020
Cited alongside, same era.
End-to-end urban driving by imitating a reinforcement learning coach
Z. Zhang, A. Liniger, D. Dai, F. Yu, and L. Van Gool · 2021
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NEAT: Neural Attention Fields for End-to-End Autonomous Driving
K. Chitta, A. Prakash, and A. Geiger · 2021
Later among the works it cites.
Enabling Spatio-temporal aggregation in Birds-Eye-View Vehicle Estimation
A. Saha, O. Mendez, C. Russell, and R. Bowden · 2021
Later among the works it cites.
FIERY: Future Instance Prediction in Bird’s-Eye View From Surround Monocular Cameras
A. Hu, Z. Murez, N. Mohan, S. Dudas, J. Hawke, V. Badrinarayanan, R. Cipolla, and A. Kendall · 2021
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Mobile: Model-based imitation learning from observation alone
R. Kidambi, J. Chang, and W. Sun · 2021
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Multi-modal fusion transformer for end-to-end autonomous driving
A. Prakash, K. Chitta, and A. Geiger · 2021
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Separating the world and ego models for self-driving
V. Sobal, A. Canziani, N. Carion, K. Cho, and Y. LeCun · 2022
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Learning from all vehicles
D. Chen and P. Krähenbühl · 2022
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Bevsegformer: Bird’s eye view semantic segmentation from arbitrary camera rigs
L. Peng, Z. Chen, Z. Fu, P. Liang, and E. Cheng · 2022
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Bird’s-eye-view panoptic segmentation using monocular frontal view images
N. Gosala and A. Valada · 2022
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BEVFormer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers
Z. Li, W. Wang, H. Li, E. Xie, C. Sima, T. Lu, Q. Yu, and J. Dai · 2022
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CARLA Maps
CARLA Team · 2022
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