Adversarial Robust Image Classification on CIFAR-10 (test) (PGD20 & CW40)
61.88Robust Accuracy (PGD-20)RobustResNet-A4
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| RobustResNet-A4#P (M)=147, #F (G)=39.4, Adversarial Training Protocol=MART2022.12 | 61.88 | 57.55 | |
| RobustResNet-A3#P (M)=75.9, #F (G)=19.9, Adversarial Training Protocol=MART2022.12 | 60.95 | 56.52 | |
| RobustResNet-A2#P (M)=39.0, #F (G)=10.8, Adversarial Training Protocol=MART2022.12 | 60.33 | 55.51 | |
| RobustResNet-A1#P (M)=19.2, #F (G)=5.11, Adversarial Training Protocol=MART2022.12 | 59.34 | 54.42 | |
| RobustResNet-A4#P (M)=147, #F (G)=39.4, Adversarial Training Protocol=SAT2022.12 | 59.01 | 57.85 | |
| RobustResNet-A3#P (M)=75.9, #F (G)=19.9, Adversarial Training Protocol=SAT2022.12 | 58.81 | 57.6 | |
| WRN-46-14#P (M)=128, #F (G)=18.6, Adversarial Training Protocol=MART2022.12 | 58.43 | 54.32 | |
| RobustResNet-A2#P (M)=39.0, #F (G)=10.8, Adversarial Training Protocol=SAT2022.12 | 58.39 | 56.99 | |
| WRN-70-16#P (M)=267, #F (G)=38.8, Adversarial Training Protocol=MART2022.12 | 58.15 | 54.37 | |
| WRN-28-10#P (M)=36.5, #F (G)=5.20, Adversarial Training Protocol=MART2022.12 | 57.69 | 52.88 | |
| RobustResNet-A1#P (M)=19.2, #F (G)=5.11, Adversarial Training Protocol=SAT2022.12 | 57.62 | 56.06 | |
| WRN-34-12#P (M)=66.5, #F (G)=9.60, Adversarial Training Protocol=MART2022.12 | 57.4 | 53.11 | |
| WRN-70-16#P (M)=267, #F (G)=38.8, Adversarial Training Protocol=SAT2022.12 | 54.12 | 50.52 | |
| WRN-46-14#P (M)=128, #F (G)=18.6, Adversarial Training Protocol=SAT2022.12 | 53.67 | 52.95 | |
| WRN-34-12#P (M)=66.5, #F (G)=9.60, Adversarial Training Protocol=SAT2022.12 | 52.85 | 51.36 | |
| WRN-28-10#P (M)=36.5, #F (G)=5.20, Adversarial Training Protocol=SAT2022.12 | 52.44 | 50.97 |