A survey on image perturbations and their influence on model robustness via adversarial attacks and defenses. It covers Convolutional Neural Networks (CNNs), Vision Transformers (ViTs), Diffusion models, Vision-Language Models (VLMs), and more.
The list provides a quick reference to all the papers covered in the survey A Survey on Image Perturbations for Model Robustness: Attacks and Defenses. It's recommended to use the paper list alongside the survey for a more comprehensive understanding.
All methods are categorized according to their purpose or the problems they aim to solve.
The paper list will be continuously updated to keep track of the latest papers.
Any suggestion, comment or related discussion is welcome.
If you find our paper list useful, we would greatly appreciate it if you could consider citing our paper:
@article{zhangsurvey,
title={A Survey on Image Perturbations for Model Robustness: Attacks and Defenses},
author={Zhang, Peng-Fei and Huang, Zi}
year = {2024},
}