Image Classification on ImageNet (Standard and Robust Accuracy)
82.33Standard AccuracyWithout defense
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| Without defenseAttack Method=random-targeted PGD-40, Architecture=ResNet-1522024.08 | 82.33 | 0.04 | |
| Without defenseAttack Method=untargeted PGD-100, Architecture=ResNet-502024.08 | 80.55 | 0.01 | |
| Without defenseAttack Method=AutoAttack, Architecture=ResNet-502024.08 | 80.55 | 0 | |
| OSCPDefense=Hybrid, Attack Method=random-targeted PGD-40, Architecture=ResNet-1522024.08 | 79.81 | 78.78 | |
| Wang et al.Defense=Diffusion Based Purification, Attack Method=random-targeted PGD-40, Architecture=ResNet-1522024.08 | 78.1 | 77.86 | |
| Amini et al.Defense=Adversarial Training, Attack Method=AutoAttack, Architecture=ConvNeXt-L2024.08 | 77.96 | 59.64 | |
| OSCPDefense=Hybrid, Attack Method=untargeted PGD-100, Architecture=ResNet-502024.08 | 77.63 | 73.89 | |
| OSCPDefense=Hybrid, Attack Method=AutoAttack, Architecture=ResNet-502024.08 | 77.63 | 74.19 | |
| Singh et al.Defense=Adversarial Training, Attack Method=AutoAttack, Architecture=ConvNeXt-L2024.08 | 77 | 57.7 | |
| DiffPureDefense=Diffusion Based Purification, Attack Method=AutoAttack, Architecture=ResNet-502024.08 | 75.77 | 73.02 | |
| Wang et al.Defense=Diffusion Based Purification, Attack Method=untargeted PGD-100, Architecture=ResNet-502024.08 | 73.53 | 72.97 |