The NVIDIA PilotNet Experiments

no code implementations • 17 Oct 2020 • Mariusz Bojarski, Chenyi Chen, Joyjit Daw, Alperen Değirmenci, Joya Deri, Bernhard Firner, Beat Flepp, Sachin Gogri, Jesse Hong, Lawrence Jackel, Zhenhua Jia, BJ Lee, Bo Liu, Fei Liu, Urs Muller, Samuel Payne, Nischal Kota Nagendra Prasad, Artem Provodin, John Roach, Timur Rvachov, Neha Tadimeti, Jesper van Engelen, Haiguang Wen, Eric Yang, Zongyi Yang

Four years ago, an experimental system known as PilotNet became the first NVIDIA system to steer an autonomous car along a roadway.

Explaining How a Deep Neural Network Trained with End-to-End Learning Steers a Car

8 code implementations • 25 Apr 2017 • Mariusz Bojarski, Philip Yeres, Anna Choromanska, Krzysztof Choromanski, Bernhard Firner, Lawrence Jackel, Urs Muller

This eliminates the need for human engineers to anticipate what is important in an image and foresee all the necessary rules for safe driving.

Autonomous Driving Self-Driving Cars

VisualBackProp: efficient visualization of CNNs

4 code implementations • 16 Nov 2016 • Mariusz Bojarski, Anna Choromanska, Krzysztof Choromanski, Bernhard Firner, Larry Jackel, Urs Muller, Karol Zieba

We furthermore justify our approach with theoretical arguments and theoretically confirm that the proposed method identifies sets of input pixels, rather than individual pixels, that collaboratively contribute to the prediction.

Self-Driving Cars

End to End Learning for Self-Driving Cars

114 code implementations • 25 Apr 2016 • 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, Karol Zieba

The system automatically learns internal representations of the necessary processing steps such as detecting useful road features with only the human steering angle as the training signal.

Lane Detection Self-Driving Cars