Alternatives and similar repositories for Transfer_attack_RAP:

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

• Framartin / lgv-geometric-transferability
  Source of the ECCV22 paper "LGV: Boosting Adversarial Example Transferability from Large Geometric Vicinity"
  ☆19Updated last year
• Alan-Qin / Transfer_attack_RAP
  Boosting the Transferability of Adversarial Attacks with Reverse Adversarial Perturbation (NeurIPS 2022)
  ☆33Updated 2 years ago
• JHL-HUST / SVRE
  Stochastic Variance Reduced Ensemble Adversarial Attack for Boosting the Adversarial Transferability
  ☆24Updated 2 years ago
• jiaxiaojunQAQ / FGSM-PGI
  Code for Prior-Guided Adversarial Initialization for Fast Adversarial Training (ECCV2022)
  ☆24Updated 2 years ago
• JindongGu / Awesome_Adversarial_Transferability
  A curated list of papers for the transferability of adversarial examples
  ☆58Updated 6 months ago
• ydc123 / Dark_Surrogate_Model
  Official code for "Boosting the Adversarial Transferability of Surrogate Model with Dark Knowledge"
  ☆11Updated last year
• zhipeng-wei / PNA-PatchOut
  ☆33Updated 6 months ago
• hcguoO0 / FIA
  code for "Feature Importance-aware Transferable Adversarial Attacks"
  ☆79Updated 2 years ago
• yihuang2016 / TAIG
  ☆21Updated 2 years ago
• xherdan76 / A-Unified-Approach-to-Interpreting-and-Boosting-Adversarial-Transferability
  A Unified Approach to Interpreting and Boosting Adversarial Transferability (ICLR2021)
  ☆29Updated 2 years ago
• ZhengyuZhao / Targeted-Transfer
  Simple yet effective targeted transferable attack (NeurIPS 2021)
  ☆48Updated 2 years ago
• psandovalsegura / pytorch-gd-uap
  Generalized Data-free Universal Adversarial Perturbations in PyTorch
  ☆19Updated 4 years ago
• JHL-HUST / VT
  Enhancing the Transferability of Adversarial Attacks through Variance Tuning
  ☆84Updated 11 months ago
• Asteriajojo / M3D
  Minimizing Maximum Model Discrepancy for Transferable Black-box Targeted Attacks(CVPR2023)
  ☆17Updated last year
• bymavis / CAS_ICLR2021
  ☆57Updated 2 years ago
• jpzhang1810 / NAA
  Official Tensorflow implementation for "Improving Adversarial Transferability via Neuron Attribution-based Attacks" (CVPR 2022)
  ☆34Updated last year
• Trustworthy-AI-Group / PGN
  [NeurIPS 2023] Boosting Adversarial Transferability by Achieving Flat Local Maxima
  ☆28Updated 11 months ago
• zj-jayzhang / Data-Free-Transfer-Attack
  Official PyTorch implementation of "Towards Efficient Data Free Black-Box Adversarial Attack" (CVPR 2022)
  ☆15Updated 2 years ago
• CGCL-codes / TransferAttackSurrogates
  The official code of IEEE S&P 2024 paper "Why Does Little Robustness Help? A Further Step Towards Understanding Adversarial Transferabili…
  ☆17Updated 5 months ago
• JHL-HUST / EMI
  Boosting Transferability through Enhanced Momentum
  ☆14Updated 11 months ago
• Alibaba-AAIG / Beyond-ImageNet-Attack
  Beyond imagenet attack (accepted by ICLR 2022) towards crafting adversarial examples for black-box domains.
  ☆60Updated 2 years ago
• Zhijin-Ge / STM
  [ACM MM 2023] Improving the Transferability of Adversarial Examples with Arbitrary Style Transfer.
  ☆17Updated 11 months ago
• qizhangli / linbp-attack
  Code for our NeurIPS 2020 paper Backpropagating Linearly Improves Transferability of Adversarial Examples.
  ☆42Updated last year
• liuye6666 / adaptive_auto_attack
  Adversarial Robustness, White-box, Adversarial Attack
  ☆50Updated 2 years ago
• val-iisc / NuAT
  Towards Efficient and Effective Adversarial Training, NeurIPS 2021
  ☆17Updated 2 years ago
• GATECH-EIC / Patch-Fool
  [ICLR 2022] "Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?" by Yonggan Fu, Shunyao Zhang, Shang Wu…
  ☆34Updated 2 years ago
• JHL-HUST / Admix
  ☆34Updated 11 months ago
• XiuchuanLi / fmixup
  Decision-based Adversarial Attack with Frequency Mixup
  ☆21Updated last year
• nblt / Sub-AT
  [CVPR 2022 oral] Subspace Adversarial Training
  ☆27Updated last year
• qizhangli / TA-Bench
  Code for our NeurIPS 2023 paper Towards Evaluating Transfer-based Attacks Systematically, Practically, and Fairly
  ☆14Updated last year