Alternatives and similar repositories for MTARD:

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

• zhipeng-wei / Self-Universality
  Enhancing the Self-Universality for Transferable Targeted Attacks [CVPR 2023 Paper]
  ☆35Updated last year
• zhipeng-wei / PNA-PatchOut
  ☆34Updated 9 months ago
• dreamflake / CFM
  [CVPR 2023] Official implementation of the Clean Feature Mixup (CFM) method
  ☆16Updated last year
• JindongGu / Awesome_Adversarial_Transferability
  A curated list of papers for the transferability of adversarial examples
  ☆65Updated 9 months ago
• Zhijin-Ge / STM
  [ACM MM 2023] Improving the Transferability of Adversarial Examples with Arbitrary Style Transfer.
  ☆18Updated last year
• jiaxiaojunQAQ / FGSM-PGI
  Code for Prior-Guided Adversarial Initialization for Fast Adversarial Training (ECCV2022)
  ☆26Updated 2 years ago
• yuyang-long / SSA
  Spectrum simulation attack (ECCV'2022 Oral) towards boosting the transferability of adversarial examples
  ☆102Updated 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…
  ☆33Updated 3 years ago
• CHENBIN99 / AdaEA
  The official repo for the paper "An Adaptive Model Ensemble Adversarial Attack for Boosting Adversarial Transferability"
  ☆40Updated last year
• qizhangli / TA-Bench
  Code for our NeurIPS 2023 paper Towards Evaluating Transfer-based Attacks Systematically, Practically, and Fairly
  ☆14Updated last year
• Trustworthy-AI-Group / PGN
  [NeurIPS 2023] Boosting Adversarial Transferability by Achieving Flat Local Maxima
  ☆30Updated last year
• yihuang2016 / TAIG
  ☆22Updated 2 years ago
• Alexkael / Randomized-Adversarial-Training
  ☆29Updated 10 months ago
• boyellow / AdaAD
  Code for the paper Boosting Accuracy and Robustness of Student Models via Adaptive Adversarial Distillation (CVPR 2023).
  ☆34Updated last year
• tly18 / TPAP
  ☆10Updated 11 months ago
• val-iisc / NuAT
  Towards Efficient and Effective Adversarial Training, NeurIPS 2021
  ☆17Updated 3 years ago
• TiJoy / Towards-Transferable-Targeted-Attack
  Codes for CVPR2020 paper "Towards Transferable Targeted Attack".
  ☆15Updated 3 years ago
• hcguoO0 / FIA
  code for "Feature Importance-aware Transferable Adversarial Attacks"
  ☆82Updated 2 years ago
• ZhengyuZhao / TransferAttackEval
  Revisiting Transferable Adversarial Images (arXiv)
  ☆123Updated last month
• zj-jayzhang / Data-Free-Transfer-Attack
  Official PyTorch implementation of "Towards Efficient Data Free Black-Box Adversarial Attack" (CVPR 2022)
  ☆18Updated 2 years ago
• JHL-HUST / SVRE
  Stochastic Variance Reduced Ensemble Adversarial Attack for Boosting the Adversarial Transferability
  ☆24Updated 2 years ago
• shighghyujie / infrared_patch_attack
  Physically Adversarial Infrared Patches with Learnable Shapes and Locations
  ☆35Updated last year
• uhiu / StyLess
  Code for the paper "StyLess: Boosting the Transferability of Adversarial Examples" (CVPR 2023)
  ☆25Updated last year
• Omenzychen / Deformable_Patch_Representation
  [ECCV 2022] Shape Matters: Deformable Patch Attack
  ☆21Updated 2 years ago
• ZFancy / IAD
  [ICLR 2022] Reliable Adversarial Distillation with Unreliable Teachers
  ☆21Updated 3 years ago
• yizhe-ang / detectron2-1
  Implements Adversarial Examples for Semantic Segmentation and Object Detection, using PyTorch and Detectron2
  ☆50Updated 4 years ago
• liuye6666 / adaptive_auto_attack
  Adversarial Robustness, White-box, Adversarial Attack
  ☆50Updated 2 years ago
• renjie3 / TUE
  Code for Transferable Unlearnable Examples
  ☆19Updated 2 years ago
• VDIGPKU / T-SEA
  [CVPR 2023] T-SEA: Transfer-based Self-Ensemble Attack on Object Detection
  ☆100Updated 6 months ago
• PKU-ML / Generalist
  CVPR 2023 generalist
  ☆15Updated last year