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adversarial-library

Library containing PyTorch implementations of various adversarial attacks and resources

alma_prox_segmentation

Code for the CVPR 2023 paper "Proximal Splitting Adversarial Attacks for Semantic Segmentation"

augmented_lagrangian_adversarial_attacks

Code for the ICCV 2021 paper "Augmented Lagrangian Adversarial Attacks"

auto-attack

Code relative to "Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks"

avc_nips_2018

Code to reproduce the attacks and defenses for the entries "JeromeR" in the NIPS 2018 Adversarial Vision Challenge

dml_cross_entropy

Code for the paper "A unifying mutual information view of metric learning: cross-entropy vs. pairwise losses" (ECCV 2020 - Spotlight)

fast_adversarial

Code for the CVPR 2019 article "Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses"

foolbox

A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX

progressive_growing_of_gans-pytorch

A PyTorch 0.4 implementation of Progressive Growing of GANs for Improved Quality, Stability and Variability (https://arxiv.org/abs/1710.10196)

pytorch-image-models

PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more

scikit-learn

scikit-learn: machine learning in Python

survey_wsl_histology