cassidylaidlaw/perceptual-advex
Code and data for the ICLR 2021 paper "Perceptual Adversarial Robustness: Defense Against Unseen Threat Models".
This project helps machine learning researchers and practitioners understand and defend against 'perceptual adversarial attacks' on image classification models. You input an image classification model and a dataset, and it outputs images that have been subtly manipulated to fool the model, along with tools to train models that are more robust to these kinds of attacks. It's for anyone building or evaluating image recognition systems who needs to ensure their models are secure against sophisticated visual trickery.
No commits in the last 6 months. Available on PyPI.
Use this if you are developing or testing image classification models and need to assess their vulnerability to visually imperceptible, but model-disrupting, alterations in images.
Not ideal if you are looking for general-purpose image augmentation or data preprocessing tools unrelated to adversarial robustness.
Stars
56
Forks
9
Language
Python
License
MIT
Category
Last pushed
Jan 18, 2022
Commits (30d)
0
Dependencies
8
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/cassidylaidlaw/perceptual-advex"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
Trusted-AI/adversarial-robustness-toolbox
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion,...
bethgelab/foolbox
A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX
DSE-MSU/DeepRobust
A pytorch adversarial library for attack and defense methods on images and graphs
cleverhans-lab/cleverhans
An adversarial example library for constructing attacks, building defenses, and benchmarking both
BorealisAI/advertorch
A Toolbox for Adversarial Robustness Research