In our team of researchers at the Max-Planck-Institute for Intelligent Systems in Tübingen we show that optical flow systems based on deep neural networks – a likely component of future autonomous cars – are vulnerable to adversarial attacks. The computer vision experts are shaking up the automotive industry by warning car manufacturers around the globe that it could take a simple color pattern to put the brakes on computer vision systems in autonomous cars. The full article can be read on the website of the Max Planck Society.
| Author(s): | Anurag Ranjan and Joel Janai and Andreas Geiger and Michael J. Black |
| Year: | 2019 |
| Month: | January |
| Day: | 01 |
| BibTeX Type: | MPI Year Book (mpi_year_book) |
| Digital: | True |
| State: | Published |
| URL: | https://www.mpg.de/14264965/is_jb_20191?c=119452 |
BibTeX
@mpi_year_book{MPG_Jahrbuch_2019_2,
title = {Colour patch could throw self-driving vehicles off track},
abstract = {In our team of researchers at the Max-Planck-Institute for Intelligent Systems in Tübingen we show that optical flow systems based on deep neural networks – a likely component of future autonomous cars – are vulnerable to adversarial attacks. The computer vision experts are shaking up the automotive industry by warning car manufacturers around the globe that it could take a simple color pattern to put the brakes on computer vision systems in autonomous cars.
The full article can be read on the website of the Max Planck Society.},
month = jan,
year = {2019},
author = {Ranjan, Anurag and Janai, Joel and Geiger, Andreas and Black, Michael J.},
url = {https://www.mpg.de/14264965/is_jb_20191?c=119452},
month_numeric = {1}
}