Description
Autonomous driving models are prone to different types of perturbations at all levels of development. Elements such as blur, noise, distortion, and coloration can vary from dataset to dataset. On this project page, we list several projects related to improving robustness for autonomous driving.
Papers
Gradient-Free Adversarial Training Against Image Corruption for Learning-based Steering.
Y. Shen, L. Zheng, M. Shu, W. Li, T. Goldstein, and M. C. Lin
Please cite our work if you found it useful: