ZSHsh98 / EPS-AD
This is the source code for Detecting Adversarial Data by Probing Multiple Perturbations Using Expected Perturbation Score (ICML2023).
☆33Updated 4 months ago
Related projects: ⓘ
- ☆35Updated last year
- [CVPR23] "Understanding and Improving Visual Prompting: A Label-Mapping Perspective" by Aochuan Chen, Yuguang Yao, Pin-Yu Chen, Yihua Zha…☆50Updated last year
- The code of the paper "Minimizing the Accumulated Trajectory Error to Improve Dataset Distillation" (CVPR2023)☆38Updated last year
- This is the official code for "Revisiting Adversarial Robustness Distillation: Robust Soft Labels Make Student Better"☆37Updated 3 years ago
- Towards Defending against Adversarial Examples via Attack-Invariant Features☆9Updated 11 months ago
- Set-level Guidance Attack: Boosting Adversarial Transferability of Vision-Language Pre-training Models. [ICCV 2023 Oral]☆45Updated last year
- ☆16Updated last year
- Code of Data-Free Knowledge Distillation via Feature Exchange and Activation Region Constraint☆15Updated 10 months ago
- ☆15Updated 4 months ago
- One Prompt Word is Enough to Boost Adversarial Robustness for Pre-trained Vision-Language Models☆31Updated 4 months ago
- ☆40Updated 7 months ago
- Official code implement of Robust Classification via a Single Diffusion Model☆49Updated 4 months ago
- [IJCAI-2021] Contrastive Model Inversion for Data-Free Knowledge Distillation☆65Updated 2 years ago
- Efficient Dataset Distillation by Representative Matching☆101Updated 6 months ago
- [NeurIPS 2021] "Class-Disentanglement and Applications in Adversarial Detection and Defense"☆43Updated 2 years ago
- [CVPR 2022 oral] Subspace Adversarial Training☆26Updated last year
- ☆22Updated last year
- Official implementation of "Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models"☆17Updated last month
- ECCV2024: Adversarial Prompt Tuning for Vision-Language Models☆19Updated last month
- ☆79Updated last year
- Respect to the input tensor instead of paramters of NN☆15Updated 2 years ago
- ☆17Updated last month
- This repository is the official implementation of Dataset Condensation with Contrastive Signals (DCC), accepted at ICML 2022.☆20Updated 2 years ago
- Official repository for "On Improving Adversarial Transferability of Vision Transformers" (ICLR 2022--Spotlight)☆69Updated last year
- [NeurIPS 2021] “When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?”☆45Updated 2 years ago
- GAMA: Generative Adversarial Multi-Object Scene Attacks (NeurIPS'22)☆12Updated last year
- [CVPR 2024] On the Diversity and Realism of Distilled Dataset: An Efficient Dataset Distillation Paradigm☆48Updated 4 months ago
- ☆24Updated 3 months ago
- ☆12Updated 2 years ago
- ☆56Updated last year