Alternatives and similar repositories for advGAN_tf2

Users that are interested in advGAN_tf2 are comparing it to the libraries listed below

• GiorgosKarantonis / Adversarial-Attacks-with-Relativistic-AdvGAN
  Using relativism to improve GAN-based Adversarial Attacks. 🦾
  ☆43Updated 2 years ago
• ctargon / AdvGAN-tf
  Tensorflow implementation of Generating Adversarial Examples with Adversarial Networks
  ☆43Updated 6 years ago
• Harry24k / CW-pytorch
  A pytorch implementation of "Towards Evaluating the Robustness of Neural Networks"
  ☆57Updated 5 years ago
• qiuweimin1332499 / AdvGAN_cifar10
  a pytorch version of AdvGAN for cifar10 dataset
  ☆10Updated 5 years ago
• greentfrapp / boundary-attack
  Implementation of the Boundary Attack algorithm as described in Brendel, Wieland, Jonas Rauber, and Matthias Bethge. "Decision-Based Adve…
  ☆96Updated 4 years ago
• Carco-git / CW_Attack_on_MNIST
  Reproduction of cw attack on pytorch with corresponding MNIST model
  ☆22Updated 4 years ago
• RjDuan / AdvCam-Hide-Adv-with-Natural-Styles
  Code for "Adversarial Camouflage: Hiding Physical World Attacks with Natural Styles" (CVPR 2020)
  ☆92Updated 2 years ago
• JHL-HUST / SI-NI-FGSM
  ☆70Updated 3 years ago
• FenHua / Adversarial-Examples
  AdvAttacks; adversarial examples; FGSM;JSMA;CW;single pixel attack; local search attack;deepfool
  ☆58Updated 5 years ago
• A-LinCui / Adversarial_Patch_Attack
  Pytorch implementation of Adversarial Patch on ImageNet (arXiv: https://arxiv.org/abs/1712.09665)
  ☆63Updated 5 years ago
• ZhaohengLi / adversarial-attacks
  Using FGSM, I-FGSM and MI-FGSM to generate and evaluate adversarial samples.
  ☆12Updated 5 years ago
• Harry24k / FGSM-pytorch
  A pytorch implementation of "Explaining and harnessing adversarial examples"
  ☆67Updated 5 years ago
• prabhant / synthesizing-robust-adversarial-examples
  My entry for ICLR 2018 Reproducibility Challenge for paper Synthesizing robust adversarial examples https://openreview.net/pdf?id=BJDH5M-…
  ☆73Updated 7 years ago
• mathcbc / advGAN_pytorch
  a Pytorch implementation of the paper "Generating Adversarial Examples with Adversarial Networks" (advGAN).
  ☆270Updated 4 years ago
• Jianbo-Lab / HSJA
  ☆85Updated 4 years ago
• JHL-HUST / VT
  Enhancing the Transferability of Adversarial Attacks through Variance Tuning
  ☆87Updated last year
• hcguoO0 / FIA
  code for "Feature Importance-aware Transferable Adversarial Attacks"
  ☆82Updated 2 years ago
• Harry24k / AEPW-pytorch
  A pytorch implementation of "Adversarial Examples in the Physical World"
  ☆17Updated 5 years ago
• ZhengyuZhao / Targeted-Transfer
  Simple yet effective targeted transferable attack (NeurIPS 2021)
  ☆51Updated 2 years ago
• xiaosen-wang / Adversarial-Examples-Paper
  Paper list of Adversarial Examples
  ☆48Updated last year
• aldahdooh / detectors_review
  ☆51Updated 3 years ago
• cg563 / low-frequency-adversarial
  ☆26Updated 2 years ago
• as791 / Adversarial-Example-Attack-and-Defense
  This repository contains the implementation of three adversarial example attack methods FGSM, IFGSM, MI-FGSM and one Distillation as defe…
  ☆127Updated 4 years ago
• MadryLab / label-consistent-backdoor-code
  Code for "Label-Consistent Backdoor Attacks"
  ☆57Updated 4 years ago
• YisenWang / MART
  Code for ICLR2020 "Improving Adversarial Robustness Requires Revisiting Misclassified Examples"
  ☆147Updated 4 years ago
• yuyang-long / SSA
  Spectrum simulation attack (ECCV'2022 Oral) towards boosting the transferability of adversarial examples
  ☆104Updated 2 years ago
• TiJoy / Towards-Transferable-Targeted-Attack
  Codes for CVPR2020 paper "Towards Transferable Targeted Attack".
  ☆15Updated 3 years ago
• qilong-zhang / Pytorch_Universal-adversarial-perturbation
  A PyTorch implementation of universal adversarial perturbation (UAP) which is more easy to understand and implement.
  ☆55Updated 3 years ago
• AdelaideAuto-IDLab / Februus
  Input Purification Defense Against Trojan Attacks on Deep Neural Network Systems
  ☆27Updated 4 years ago
• HangJie720 / Ensemble_Adversarial_Attack
  Ensemble Adversarial Black-Box Attacks against Deep Learning Systems Trained by MNIST, USPS and GTSRB Datasets
  ☆33Updated 5 years ago