🔥[2024-07-24] Papers of ICML 2024 have been updated here!
🔥[2024-07-04] Papers of CVPR 2024 have been updated here!
Title | Publish | Repo | Paper | Summary |
---|---|---|---|---|
Content-based Unrestricted Adversarial Attack | NeurIPS | - | summary | |
Diff-PGD: Diffusion-Based Adversarial Sample Generation for Improved Stealthiness and Controllability | NeurIPS | summary | ||
Downstream-agnostic Adversarial Examples | ICCV | |||
AdvDiffuser: Natural Adversarial Example Synthesis with Diffusion Models | ICCV | summary | ||
Frequency-aware GAN for Adversarial Manipulation Generation | ICCV | - | ||
AdvDiff: Generating Unrestricted Adversarial Examples using Diffusion Models | - | summary | ||
Diffusion Models for Imperceptible and Transferable Adversarial Attack | - | |||
Improving Adversarial Transferability by Stable Diffusion | - | - | ||
Semantic Adversarial Attacks via Diffusion Models | BMVC | summary |
Title | Publish | Repo | Paper | Summary |
---|---|---|---|---|
Towards Feature Space Adversarial Attack | ** | summary |
Title | Publish | Repo | Paper | Summary |
---|---|---|---|---|
Unrestricted Adversarial Examples via Semantic Manipulation | ICLR | summary | ||
SemanticAdv: Generating Adversarial Examples via Attribute-conditioned Image Editing | ECCV | summary | ||
Colorfool: Semantic adversarial colorization | CVPR | - | - | - |
Title | Publish | Repo | Paper | Summary |
---|---|---|---|---|
Semantic Adversarial Attacks: Parametric Transformations That Fool Deep Classifiers | ICCV | summary | ||
Rob-GAN: Generator, Discriminator, and Adversarial Attacker | CVPR | summary | ||
ADef: an Iterative Algorithm to Construct Adversarial Deformations | ICLR | - | - | - |
AdvGAN++: Harnessing Latent Layers for Adversary Generation | CVPRW | summary | ||
One pixel attack for fooling deep neural networks | IEEE TEVC | - | - | - |
Title | Publish | Repo | Paper | Summary |
---|---|---|---|---|
Intriguing Properties of Neural Networks. | ICLR 2014 | - | summary | |
FGSM: Explaining and Harnessing Adversarial Examples | ICLR 2015 | - | summary | |
Deepfool: a simple and accurate method to fool deep neural networks | CVPR 2016 | - | ||
Universal adversarial perturbations | CVPR 2017 | - | ||
Towards evaluating the robustness of neural networks | 2017 IEEE Symposium on Security and Privacy (SP) | - | - | - |
Ensemble Adversarial Training: Attacks and Defenses | ICLR 2018 | - | - | |
PGD: Towards Deep Learning Models Resistant to Adversarial Attacks | ICLR 2018 | - | ||
Generating Natural Adversarial Examples | ICLR 2018 | summary | ||
Constructing Unrestricted Adversarial Examples with Generative Models | NeurIPS 2018 | summary | ||
NAG: Network for Adversary Generation | CVPR 2018 | summary | ||
Semantic Adversarial Examples | CVPRW 2018 | summary | ||
AdvGAN: Generating adversarial examples with adversarial networks | IJCAI 2018 | summary | ||
ATN: Learning to Attack: Adversarial Transformation Networks | AAAI 2018 | summary |