google-research / preprocessor-aware-black-box-attack
☆20Updated last year
Related projects ⓘ
Alternatives and complementary repositories for preprocessor-aware-black-box-attack
- Official Code for Efficient and Effective Augmentation Strategy for Adversarial Training (NeurIPS-2022)☆15Updated last year
- ☆10Updated last year
- Certified Patch Robustness via Smoothed Vision Transformers☆41Updated 2 years ago
- Code for a research paper "Part-Based Models Improve Adversarial Robustness" (ICLR 2023)☆22Updated last year
- Code for the paper Boosting Accuracy and Robustness of Student Models via Adaptive Adversarial Distillation (CVPR 2023).☆31Updated last year
- ☆12Updated 2 years ago
- [ICML2023] Revisiting Data-Free Knowledge Distillation with Poisoned Teachers☆22Updated 4 months ago
- ☆29Updated 2 years ago
- ☆22Updated last year
- Official repository for "On Improving Adversarial Transferability of Vision Transformers" (ICLR 2022--Spotlight)☆70Updated 2 years ago
- ☆54Updated last year
- Adversarial Augmentation Against Adversarial Attacks☆27Updated last year
- Official code for the ICCV2023 paper ``One-bit Flip is All You Need: When Bit-flip Attack Meets Model Training''☆14Updated last year
- Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses, NeurIPS Spotlight 2020☆24Updated 3 years ago
- SEAT☆20Updated last year
- The official implementation of ECCV'24 paper "To Generate or Not? Safety-Driven Unlearned Diffusion Models Are Still Easy To Generate Uns…☆58Updated 2 weeks ago
- [ICLR 2024] Inducing High Energy-Latency of Large Vision-Language Models with Verbose Images☆24Updated 9 months ago
- kyleliang919 / Uncovering-the-Connections-BetweenAdversarial-Transferability-and-Knowledge-Transferabilitycode for ICML 2021 paper in which we explore the relationship between adversarial transferability and knowledge transferability.☆17Updated last year
- Code corresponding to the paper: "On the Robustness of Vision Transformers": https://arxiv.org/abs/2104.02610☆23Updated 7 months ago
- Helper-based Adversarial Training: Reducing Excessive Margin to Achieve a Better Accuracy vs. Robustness Trade-off☆29Updated 2 years ago
- GreedyFool (NIPS2020) official code for saprse adversarial attack☆35Updated 4 years ago
- Code for the paper "A Light Recipe to Train Robust Vision Transformers" [SaTML 2023]☆52Updated last year
- [NeurIPS2021] Code Release of Learning Transferable Perturbations☆26Updated 2 years ago
- Code for our ICLR 2023 paper Making Substitute Models More Bayesian Can Enhance Transferability of Adversarial Examples.☆18Updated last year
- Code for Boosting fast adversarial training with learnable adversarial initialization (TIP2022)☆29Updated last year
- Official Implementation for PlugIn Inversion☆15Updated 3 years ago
- ☆10Updated 8 months ago
- Data-free knowledge distillation using Gaussian noise (NeurIPS paper)☆15Updated last year
- This repository contains the ViewFool and ImageNet-V proposed by the paper “ViewFool: Evaluating the Robustness of Visual Recognition to …☆27Updated 11 months ago
- Data-Efficient Backdoor Attacks☆18Updated 2 years ago