This repository contains the datasets and some code for the paper Benchmarking Neural Network Robustness to Common Corruptions and Perturbations by Dan Hendrycks and Tom Dietterich.
Requires Python 3+ and PyTorch 0.3+.
Download Tiny ImageNet-C here.
ImageNet-P sequences are MP4s not GIFs. The spatter perturbation sequence is a validation sequence.
Download Tiny ImageNet-P here.
If you find this useful in your research, please consider citing:
@article{hendrycks2018robustness,
title={Benchmarking Neural Network Robustness to Common Corruptions and Perturbations},
author={Dan Hendrycks and Thomas Dietterich},
journal={arXiv preprint arXiv:1807.01697},
year={2018}
}