Adversarial Differentiable Data Augmentation for Autonomous Systems
This repository provides the official PyTorch implementation of the ICRA 2021 paper:
Adversarial Differentiable Data Augmentation for Autonomous Systems
Author: Manli Shu, Yu Shen, Ming C Lin, Tom Goldstein
Environment
The code has been tested on:
- python == 3.7.9
- pytorch == 1.10.0
- torchvision == 0.8.2
- kornia == 0.6.2
More dependencies can be found at./requirements.txt
Hardware requirements:
- The default training and testing setting requires 1 GPU.
Data
Datasets appeared in our paper can be downloaded/generated by following the directions in this page.
Note: The “distortion” factor is added differently in our work, for which we cropped out the zero-padding around the distorted images. To reproduce the results in our paper, the