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Most existing approaches to autonomous driving fall into one of two categories: modular pipelines, that build an extensive model of the environment, and imitation learning approaches, that map images directly to control outputs.
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Pid control system analysis, design, and technology
Kiam Heong Ang, Gregory Chong, and Yun Li · 2005
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Stanley: The robot that won the DARPA grand challenge
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Vision meets robotics: The KITTI dataset
A. Geiger, P. Lenz, C. Stiller, and R. Urtasun · 2013
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Understanding high-level semantics by modeling traffic patterns
H. Zhang, A. Geiger, and R. Urtasun · 2013
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Making Bertha drive — An autonomous journey on a historic route
J. Ziegler, P. Bender, M. Schreiber, H. Lategahn, T. Strauss, C. Stiller, T. Dang, U. Franke, N. Appenrodt, and C. G. Keller · 2014
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3D Traffic Scene Understanding from Movable Platforms
A. Geiger, M. Lauer, C. Wojek, C. Stiller, and R. Urtasun · 2014
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
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Learning phrase representations using RNN encoder-decoder for statistical machine translation
K. Cho, B. van Merrienboer, Ç. Gülçehre, F. Bougares, H. Schwenk, and Y. Bengio · 2014
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Adam: A method for stochastic optimization
D. Kingma and J. Ba · 2014
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Deepdriving: Learning affordance for direct perception in autonomous driving
C. Chen, A. Seff, A. Kornhauser, and J. Xiao · 2015
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Faster R-CNN: Towards real-time object detection with region proposal networks
S. Ren, K. He, R. Girshick, and J. Sun · 2015
Grad-cam: Visual explanations from deep networks via gradient-based localization
R. R. Selvaraju, M. Cogswell, A. Das, R. Vedantam, D. Parikh, and D. Batra · 2016
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Mask R-CNN
K. He, G. Gkioxari, P. Dollár, and R. Girshick · 2017
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Fully convolutional instance-aware semantic segmentation
Y. Li, H. Qi, J. Dai, X. Ji, and Y. Wei · 2017
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End-to-end learning of geometry and context for deep stereo regression
A. Kendall, H. Martirosyan, S. Dasgupta, and P. Henry · 2017
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PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume
D. Sun, X. Yang, M.-Y. Liu, and J. Kautz · 2017
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Deep learning algorithm for autonomous driving using GoogLeNet
M. Al-Qizwini, I. Barjasteh, H. Al-Qassab, and H. Radha · 2017
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Cited alongside, same era.
Going deeper with convolutions
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich · 2015
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Evolving a general electronic stability program for car simulated in TORCS
J. Huang, I. Tanev, and K. Shimohara · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
S. Ioffe and C. Szegedy · 2015
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Artificial intelligence: a modern approach
S. J. Russell and P. Norvig · 2016
Cited alongside, same era.
You only look once: Unified, real-time object detection
J. Redmon, S. Divvala, R. Girshick, and A. Farhadi · 2016
Cited alongside, same era.
Stereo matching by training a convolutional neural network to compare image patches
J. Žbontar and Y. LeCun · 2016
Cited alongside, same era.
Later among the works it cites.
Gradient-free policy architecture search and adaptation
S. Ebrahimi, A. Rohrbach, and T. Darrell · 2017
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CARLA: An open urban driving simulator
A. Dosovitskiy, G. Ros, F. Codevilla, A. Lopez, and V. Koltun · 2017
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End-to-end learning of driving models from large-scale video datasets
H. Xu, Y. Gao, F. Yu, and T. Darrell · 2017
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And the award for most nauseating self-driving car goes to …
R. Metz · 2018
Closest in time.
Planning and decision-making for autonomous vehicles
W. Schwarting, J. Alonso-Mora, and D. Rus · 2018
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End-to-end driving via conditional imitation learning
F. Codevilla, M. Müller, A. Dosovitskiy, A. Lopez, and V. Koltun · 2018
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The Architectural Implications of Autonomous Driving: Constraints and Acceleration
S. Lin, Y. Zhang, C. Hsu, M. Skach, M. Haque, L. Tang, J. Mars · 2018
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Sim4cv: A photo-realistic simulator for computer vision applications
M. Müller, V. Casser, J. Lahoud, N. Smith, and B. Ghanem · 2018
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Driving policy transfer via modularity and abstraction
M. Müller, A. Dosovitskiy, B. Ghanem, and V. Koltun · 2018
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