SOTAVerified

Adversarial Defense

Competitions with currently unpublished results:

Papers

Showing 101125 of 403 papers

TitleStatusHype
CAAD 2018: Generating Transferable Adversarial ExamplesCode0
Adversarial Robustness of Stabilized NeuralODEs Might be from Obfuscated GradientsCode0
Feature Denoising for Improving Adversarial RobustnessCode0
Adversarial-Playground: A Visualization Suite Showing How Adversarial Examples Fool Deep LearningCode0
Bridging Robustness and Generalization Against Word Substitution Attacks in NLP via the Growth Bound Matrix ApproachCode0
Exploring Adversarially Robust Training for Unsupervised Domain AdaptationCode0
Adaptive Modeling Against Adversarial AttacksCode0
Adversarial Defense by Suppressing High-frequency ComponentsCode0
Certified Defenses against Adversarial ExamplesCode0
Characterizing Adversarial Subspaces Using Local Intrinsic DimensionalityCode0
Accidental Misalignment: Fine-Tuning Language Models Induces Unexpected VulnerabilityCode0
Fast Bayesian Uncertainty Estimation and Reduction of Batch Normalized Single Image Super-Resolution NetworkCode0
Game Theoretic Mixed Experts for Combinational Adversarial Machine LearningCode0
Gotta Catch 'Em All: Using Honeypots to Catch Adversarial Attacks on Neural NetworksCode0
AOGNets: Compositional Grammatical Architectures for Deep LearningCode0
Beyond Pretrained Features: Noisy Image Modeling Provides Adversarial DefenseCode0
A Few Large Shifts: Layer-Inconsistency Based Minimal Overhead Adversarial Example DetectionCode0
Constructing Semantics-Aware Adversarial Examples with a Probabilistic PerspectiveCode0
Adversarially Robust Prototypical Few-shot Segmentation with Neural-ODEsCode0
Countering Adversarial Images using Input TransformationsCode0
Robustifying Point Cloud Networks by RefocusingCode0
A Game-Based Approximate Verification of Deep Neural Networks with Provable GuaranteesCode0
ResNets Ensemble via the Feynman-Kac Formalism to Improve Natural and Robust AccuraciesCode0
DAD++: Improved Data-free Test Time Adversarial DefenseCode0
Bayesian Learning with Information Gain Provably Bounds Risk for a Robust Adversarial DefenseCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1WRN-28-10Accuracy90.03Unverified
2Diffusion ClassifierAccuracy89.85Unverified
3Stochastic-LWTA/PGD/WideResNet-34-10Accuracy84.3Unverified
4Ours (Stochastic-LWTA/PGD/WideResNet-34-5)Accuracy83.4Unverified
5Ours (Stochastic-LWTA/PGD/WideResNet-34-1)Accuracy81.87Unverified
6ResNet18 (TRADES-ANCRA/PGD-40)Accuracy81.7Unverified
7Stochastic-LWTA/PGD/WideResNet-34-5Attack: AutoAttack81.22Unverified
8PCL (against PGD, white box)Accuracy46.7Unverified
#ModelMetricClaimedVerifiedStatus
1SAT-EfficientNet-L1Accuracy58.6Unverified
2LLR-ResNet-152Accuracy47Unverified
3ResNet-152 free-m=4Accuracy36Unverified
4ResNet-101 free-m=4Accuracy34.3Unverified
5ResNet-50 free-m=4Accuracy31.8Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet101Accuracy99.8Unverified
2InceptionV3Accuracy98.6Unverified
3Feature DenoisingAccuracy49.5Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet-152 DenoiseAccuracy42.8Unverified
2ResNeXt-101 DenoiseAllAccuracy40.4Unverified
3ResNet-152Accuracy39Unverified
#ModelMetricClaimedVerifiedStatus
1Defense GANAccuracy0.85Unverified
2PuVAEAccuracy0.81Unverified
#ModelMetricClaimedVerifiedStatus
1Feature DenoisingAccuracy50.6Unverified
#ModelMetricClaimedVerifiedStatus
1Auto Encoder-Block Switching defense with GradCAMAccuracy 88.54Unverified