Alternatives and similar repositories for Universal_Adversarial_Perturbation_pytorch

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

• csdongxian / skip-connections-matter
  Codes for ICLR 2020 paper "Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets"
  ☆70Updated 4 years ago
• BXuan694 / Universal-Adversarial-Perturbation
  This is PyTorch Implementation of Universal Adversarial Perturbation (https://arxiv.org/abs/1610.08401)
  ☆46Updated 6 years ago
• bymavis / CAS_ICLR2021
  ☆58Updated 2 years ago
• ermongroup / ODS
  Code for "Diversity can be Transferred: Output Diversification for White- and Black-box Attacks"
  ☆53Updated 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
• giladcohen / NNIF_adv_defense
  Detection of adversarial examples using influence functions and nearest neighbors
  ☆36Updated 2 years ago
• NetoPedro / Universal-Adversarial-Perturbations-Pytorch
  Implementation of https://arxiv.org/abs/1610.08401 for the CS-E4070 - Special Course in Machine Learning and Data Science: Advanced Topic…
  ☆62Updated 5 years ago
• YisenWang / MART
  Code for ICLR2020 "Improving Adversarial Robustness Requires Revisiting Misclassified Examples"
  ☆150Updated 4 years ago
• qizhangli / linbp-attack
  Code for our NeurIPS 2020 paper Backpropagating Linearly Improves Transferability of Adversarial Examples.
  ☆42Updated 2 years ago
• qilong-zhang / Patch-wise-iterative-attack
  Patch-wise iterative attack (accepted by ECCV 2020) to improve the transferability of adversarial examples.
  ☆92Updated 3 years ago
• hcguoO0 / FIA
  code for "Feature Importance-aware Transferable Adversarial Attacks"
  ☆82Updated 3 years ago
• thu-ml / Prior-Guided-RGF
  ☆41Updated last year
• JHL-HUST / VT
  Enhancing the Transferability of Adversarial Attacks through Variance Tuning
  ☆88Updated last year
• dongyp13 / Translation-Invariant-Attacks
  The translation-invariant adversarial attack method to improve the transferability of adversarial examples.
  ☆141Updated last year
• vtddggg / CAA
  The implementation of our paper: Composite Adversarial Attacks (AAAI2021)
  ☆30Updated 3 years ago
• CUAI / Intermediate-Level-Attack
  [ICCV 2019] Enhancing Adversarial Example Transferability with an Intermediate Level Attack (https://arxiv.org/abs/1907.10823)
  ☆79Updated 5 years ago
• dongyp13 / Adversarial-Distributional-Training
  Adversarial Distributional Training (NeurIPS 2020)
  ☆63Updated 4 years ago
• dvlab-research / LBGAT
  Learnable Boundary Guided Adversarial Training (ICCV2021)
  ☆38Updated 7 months ago
• qilong-zhang / Pytorch_Universal-adversarial-perturbation
  A PyTorch implementation of universal adversarial perturbation (UAP) which is more easy to understand and implement.
  ☆56Updated 3 years ago
• tobylyf / adv-attack
  Adversarial attacks including DeepFool and C&W
  ☆13Updated 6 years ago
• liuye6666 / adaptive_auto_attack
  Adversarial Robustness, White-box, Adversarial Attack
  ☆50Updated 3 years ago
• zjfheart / Friendly-Adversarial-Training
  Attacks Which Do Not Kill Training Make Adversarial Learning Stronger (ICML2020 Paper)
  ☆125Updated last year
• Ping-C / certifiedpatchdefense
  Repository for Certified Defenses for Adversarial Patch ICLR-2020
  ☆33Updated 4 years ago
• Jianbo-Lab / HSJA
  ☆85Updated 4 years ago
• cmhcbb / attackbox
  ☆60Updated 3 years ago
• cihangxie / DI-2-FGSM
  Improving Transferability of Adversarial Examples with Input Diversity
  ☆164Updated 6 years ago
• Muzammal-Naseer / NRP
  Official repository for "A Self-supervised Approach for Adversarial Robustness" (CVPR 2020--Oral)
  ☆100Updated 4 years ago
• haizhongzheng / ATTA
  ATTA (Efficient Adversarial Training with Transferable Adversarial Examples)
  ☆36Updated 4 years ago
• JHL-HUST / SI-NI-FGSM
  ☆71Updated 4 years ago
• greentfrapp / boundary-attack
  Implementation of the Boundary Attack algorithm as described in Brendel, Wieland, Jonas Rauber, and Matthias Bethge. "Decision-Based Adve…
  ☆98Updated 4 years ago