bethgelab / robust-vision-benchmark
Robust Vision Benchmark
☆22Updated 6 years ago
Related projects ⓘ
Alternatives and complementary repositories for robust-vision-benchmark
- Code for "Robustness May Be at Odds with Accuracy"☆93Updated last year
- Provable Robustness of ReLU networks via Maximization of Linear Regions [AISTATS 2019]☆31Updated 4 years ago
- NIPS Adversarial Vision Challenge☆41Updated 6 years ago
- Code for "Testing Robustness Against Unforeseen Adversaries"☆80Updated 3 months ago
- A powerful white-box adversarial attack that exploits knowledge about the geometry of neural networks to find minimal adversarial perturb…☆11Updated 4 years ago
- Analysis of Adversarial Logit Pairing☆60Updated 6 years ago
- Investigating the robustness of state-of-the-art CNN architectures to simple spatial transformations.☆49Updated 5 years ago
- Provably defending pretrained classifiers including the Azure, Google, AWS, and Clarifai APIs☆96Updated 3 years ago
- Source code for the paper "Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness"☆26Updated 4 years ago
- Notebooks for reproducing the paper "Computer Vision with a Single (Robust) Classifier"☆128Updated 5 years ago
- ☆86Updated 3 months ago
- Adversarially Robust Neural Network on MNIST.☆64Updated 2 years ago
- Randomized Smoothing of All Shapes and Sizes (ICML 2020).☆50Updated 4 years ago
- A community-run reference for state-of-the-art adversarial example defenses.☆49Updated 3 weeks ago
- Benchmark for LP-relaxed robustness verification of ReLU-networks☆40Updated 5 years ago
- Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks, in ICCV 2019☆59Updated 5 years ago
- Official implementation for paper: A New Defense Against Adversarial Images: Turning a Weakness into a Strength☆37Updated 4 years ago
- ☆20Updated 3 months ago
- Code for our NeurIPS 2019 *spotlight* "Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers"☆223Updated 5 years ago
- Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation [NeurIPS 2017]☆18Updated 6 years ago
- Pytorch Adversarial Attack Framework☆78Updated 5 years ago
- Datasets for the paper "Adversarial Examples are not Bugs, They Are Features"☆185Updated 4 years ago
- Interfaces for defining Robust ML models and precisely specifying the threat models under which they claim to be secure.☆62Updated 5 years ago
- Code for Stability Training with Noise (STN)☆21Updated 3 years ago
- Public code for a paper "Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks."☆34Updated 5 years ago
- Official repository for our NeurIPS 2021 paper "Unadversarial Examples: Designing Objects for Robust Vision"☆103Updated 3 months ago
- A PyTorch baseline attack example for the NIPS 2017 adversarial competition☆85Updated 7 years ago
- Codebase for "Exploring the Landscape of Spatial Robustness" (ICML'19, https://arxiv.org/abs/1712.02779).☆26Updated 5 years ago
- ☆26Updated 5 years ago
- Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)☆99Updated 2 years ago