Fetching the paper…
Reading the bibliography…
Deep convolutional neural networks (CNNs) have been shown to perform extremely well at a variety of tasks including subtasks of autonomous driving such as image segmentation and object classification.
Alvinn: An autonomous land vehicle in a neural network
D. A. Pomerleau · 1989
Earlier work this paper cites.
Multitask learning
R. Caruana · 1997
Earlier work this paper cites.
Long short-term memory
S. Hochreiter and J. Schmidhuber · 1997
Earlier work this paper cites.
Off-road obstacle avoidance through end-to-end learning
Y. Lecun, U. Muller, J. Ben, E. Cosatto, and B. Flepp · 2005
Earlier work this paper cites.
Long-term Recurrent Convolutional Networks for Visual Recognition and Description
J. Donahue, L. A. Hendricks, M. Rohrbach, S. Venugopalan, S. Guadarrama, K. Saenko, and T. Darrell · 2014
Earlier work this paper cites.
Deep Visual-Semantic Alignments for Generating Image Descriptions
A. Karpathy and L. Fei-Fei · 2014
Earlier work this paper cites.
Adam: A Method for Stochastic Optimization
D. P. Kingma and J. Ba · 2014
Earlier work this paper cites.
Very Deep Convolutional Networks for Large-Scale Image Recognition
K. Simonyan and A. Zisserman · 2014
Earlier work this paper cites.
Energy-efficient hog-based object detection at 1080hd 60 fps with multi-scale support
A. Suleiman and V. Sze · 2014
Cited alongside, same era.
DeepDriving: Learning Affordance for Direct Perception in Autonomous Driving
C. Chen, A. Seff, A. Kornhauser, and J. Xiao · 2015
Cited alongside, same era.
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
S. Ioffe and C. Szegedy · 2015
Cited alongside, same era.
3d lidar-based static and moving obstacle detection in driving environments: an approach based on voxels and multi-region ground planes
A. Asvadi, C. Premebida, P. Peixoto, and U. Nunes · 2016
Cited alongside, same era.
End to End Learning for Self-Driving Cars
M. Bojarski, D. Del Testa, D. Dworakowski, B. Firner, B. Flepp, P. Goyal, L. D. Jackel, M. Monfort, U. Muller, J. Zhang, X. Zhang, J. Zhao, and K. Zieba · 2016
Cited alongside, same era.
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size
F. N. Iandola, S. Han, M. W. Moskewicz, K. Ashraf, W. J. Dally, and K. Keutzer · 2016
Later among the works it cites.
Spatially Supervised Recurrent Convolutional Neural Networks for Visual Object Tracking
G. Ning, Z. Zhang, C. Huang, Z. He, X. Ren, and H. Wang · 2016
Later among the works it cites.
SqueezeDet: Unified, Small, Low Power Fully Convolutional Neural Networks for Real-Time Object Detection for Autonomous Driving
B. Wu, F. Iandola, P. H. Jin, and K. Keutzer · 2016
Later among the works it cites.
End-to-end Learning of Driving Models from Large-scale Video Datasets
H. Xu, Y. Gao, F. Yu, and T. Darrell · 2016
Later among the works it cites.
Multi-Modal Multi-Task Deep Learning for Autonomous Driving
S. Chowdhuri, T. Pankaj, and K. Zipser · 2017
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Multi-View 3D Object Detection Network for Autonomous Driving
X. Chen, H. Ma, J. Wan, B. Li, and T. Xia · 2016
Cited alongside, same era.
Deeplanes: End-to-end lane position estimation using deep neural networks
A. Gurghian, T. Koduri, S. V. Bailur, K. J. Carey, and V. N. Murali · 2016
Cited alongside, same era.
F. Codevilla, M. Müller, A. Dosovitskiy, A. López, and V. Koltun · 2017
Closest in time.
3D Visual Perception for Self-Driving Cars using a Multi-Camera System: Calibration, Mapping, Localization, and Obstacle Detection
C. Häne, L. Heng, G. H. Lee, F. Fraundorfer, P. Furgale, T. Sattler, and M. Pollefeys · 2017
Closest in time.