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06/22/2023
Robust Semantic Segmentation: Strong Adversarial Attacks and Fast Training of Robust Models
While a large amount of work has focused on designing adversarial attack...
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03/03/2023
Revisiting Adversarial Training for ImageNet: Architectures, Training and Generalization across Threat Models
While adversarial training has been extensively studied for ResNet archi...
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02/20/2023
Seasoning Model Soups for Robustness to Adversarial and Natural Distribution Shifts
Adversarial training is widely used to make classifiers robust to a spec...
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02/14/2023
A modern look at the relationship between sharpness and generalization
Sharpness of minima is a promising quantity that can correlate with gene...
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10/21/2022
Diffusion Visual Counterfactual Explanations
Visual Counterfactual Explanations (VCEs) are an important tool to under...
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10/10/2022
Revisiting adapters with adversarial training
While adversarial training is generally used as a defense mechanism, rec...
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09/14/2022
On the interplay of adversarial robustness and architecture components: patches, convolution and attention
In recent years novel architecture components for image classification h...
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05/16/2022
Sparse Visual Counterfactual Explanations in Image Space
Visual counterfactual explanations (VCEs) in image space are an importan...
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02/28/2022
Evaluating the Adversarial Robustness of Adaptive Test-time Defenses
Adaptive defenses that use test-time optimization promise to improve rob...
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05/26/2021
Adversarial robustness against multiple l_p-threat models at the price of one and how to quickly fine-tune robust models to another threat model
Adversarial training (AT) in order to achieve adversarial robustness wrt...
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03/01/2021
Mind the box: l_1-APGD for sparse adversarial attacks on image classifiers
We show that when taking into account also the image domain [0,1]^d, est...
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10/19/2020
RobustBench: a standardized adversarial robustness benchmark
Evaluation of adversarial robustness is often error-prone leading to ove...
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06/23/2020
Sparse-RS: a versatile framework for query-efficient sparse black-box adversarial attacks
A large body of research has focused on adversarial attacks which requir...
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03/03/2020
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks
The field of defense strategies against adversarial attacks has signific...
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11/29/2019
Square Attack: a query-efficient black-box adversarial attack via random search
We propose the Square Attack, a new score-based black-box l_2 and l_∞ ad...
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09/11/2019
Sparse and Imperceivable Adversarial Attacks
Neural networks have been proven to be vulnerable to a variety of advers...
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07/03/2019
Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack
The evaluation of robustness against adversarial manipulation of neural ...
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05/27/2019
Provable robustness against all adversarial l_p-perturbations for p≥ 1
In recent years several adversarial attacks and defenses have been propo...
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03/27/2019
Scaling up the randomized gradient-free adversarial attack reveals overestimation of robustness using established attacks
Modern neural networks are highly non-robust against adversarial manipul...
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11/28/2018
A randomized gradient-free attack on ReLU networks
It has recently been shown that neural networks but also other classifie...
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10/17/2018