This pull request was merged! Please use the original mmdetection toolbox for robustness benchmarking!
We will keep this fork for a while but may evantually delete it in the future.
This repository contains a fork of the mmdetection toolbox with code to test models on coprrupted images. It was created as a part of the Robust Detection Benchmark Suite and has been submitted to mmdetection as pull request.
The benchmarking toolkit is part of the paper Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming.
For more information how to evaluate models on corrupted images and results for a set of standard models please refer to ROBUSTNESS_BENCHMARKING.md.
For informations on mmdetection please refer to the mmdetection readme.
This project is released under the Apache 2.0 license.
Results for standard models are available in ROBUSTNESS_BENCHMARKING.md. For up-to-date results have a look at the official benchmark homepage.
Please refer to INSTALL.md for installation and dataset preparation.
Please see GETTING_STARTED.md for the basic usage of MMDetection.
Plase see ROBUSTNESS_BENCHMARKING.md for instructions on robustness benchmarking.
If you use this toolbox or benchmark in your research, please cite this project.
@article{michaelis2019winter,
title={Benchmarking Robustness in Object Detection:
Autonomous Driving when Winter is Coming},
author={Michaelis, Claudio and Mitzkus, Benjamin and
Geirhos, Robert and Rusak, Evgenia and
Bringmann, Oliver and Ecker, Alexander S. and
Bethge, Matthias and Brendel, Wieland},
journal={arXiv:1907.07484},
year={2019}
}
This repo is currently maintained by Claudio Michaelis (@michaelisc).
For questions regarding mmdetection please visit the official repository.