This repository contains the implementation of the paper “Towards Frequency-Based Explanation for Robust CNN” arxiv. It primarly deals the extent to which image features are robust in the frequency domain.
- It is recommended to setup a fresh virtual environment first.
python -m venv env source activate env/bin/activate
- Install the torchattacks package
pip install torchattacks
- Run the
The original paper implemented the attacks using a VGG 19 model. However, due to memory constraints I did it using ResNet 18. Here I have provided a fine-tuned version of ResNet 18 which is pre-trained on ImageNet. The checkpoint can be downloaded using this link.
This is not an official implementation of the paper. I am not associated with the authors of the paper or Lab in any manner whatsoever and I don’t claim credit for any of the algorithms proposed in the paper.