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Adversarial Purification

A class of adversarial defense methods that remove adversarial perturbations using a generative model.

Papers

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Showing 1–25 of 65 papers

TitleStatusHype
DiffCAP: Diffusion-based Cumulative Adversarial Purification for Vision Language Models—0
Fighting Fire with Fire (F3): A Training-free and Efficient Visual Adversarial Example Purification Method in LVLMs—0
How Do Diffusion Models Improve Adversarial Robustness?—0
Towards more transferable adversarial attack in black-box manner—0
FlowPure: Continuous Normalizing Flows for Adversarial PurificationCode1
Diffusion-based Adversarial Purification from the Perspective of the Frequency Domain—0
Defending Against Frequency-Based Attacks with Diffusion Models—0
LISArD: Learning Image Similarity to Defend Against Gray-box Adversarial AttacksCode0
Model-Free Adversarial Purification via Coarse-To-Fine Tensor Network Representation—0
VideoPure: Diffusion-based Adversarial Purification for Video RecognitionCode0
Gradient-Free Adversarial Purification with Diffusion Models—0
Divide and Conquer: Heterogeneous Noise Integration for Diffusion-based Adversarial Purification—0
Adversarial Purification by Consistency-aware Latent Space Optimization on Data Manifolds—0
Pre-trained Multiple Latent Variable Generative Models are good defenders against Adversarial AttacksCode0
Random Sampling for Diffusion-based Adversarial PurificationCode0
Adversarial Attacks and Robust Defenses in Speaker Embedding based Zero-Shot Text-to-Speech System—0
Improving Adversarial Robustness for 3D Point Cloud Recognition at Test-Time through Purified Self-Training—0
Detecting and Defending Against Adversarial Attacks on Automatic Speech Recognition via Diffusion ModelsCode0
High-Frequency Anti-DreamBooth: Robust Defense against Personalized Image SynthesisCode0
LoRID: Low-Rank Iterative Diffusion for Adversarial Purification—0
Instant Adversarial Purification with Adversarial Consistency Distillation—0
MsMemoryGAN: A Multi-scale Memory GAN for Palm-vein Adversarial Purification—0
Classifier Guidance Enhances Diffusion-based Adversarial Purification by Preserving Predictive Information—0
Adversarially Robust Industrial Anomaly Detection Through Diffusion Model—0
Guardians of Image Quality: Benchmarking Defenses Against Adversarial Attacks on Image Quality MetricsCode1
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