Image Classification on CIFAR-10 L2 Robustness (epsilon=0.5, test)
96.09Standard AccuracyWang et al.
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| Wang et al.Type=AT, Architecture=WideResNet-70-162023.07 | 96.09 | 86.72 | |
| ScoreOptType=AP, Architecture=WideResNet-70-162023.07 | 95.18 | 87.11 | |
| ScoreOptType=AP, Architecture=WideResNet-28-102023.07 | 94.99 | 86.78 | |
| Augustin et al.Type=AT, Architecture=WideResNet-28-102023.07 | 93.96 | 86.14 | |
| Rebuffi et al.Type=AT, Architecture=WideResNet-70-162023.07 | 92.41 | 86.24 | |
| Nie et al.Type=AP, Architecture=WideResNet-70-162023.07 | 92.15 | 84.8 | |
| Rebuffi et al.Type=AT, Architecture=WideResNet-28-102023.07 | 91.79 | 85.05 | |
| Nie et al.Type=AP, Architecture=WideResNet-28-102023.07 | 91.41 | 82.11 | |
| Sehwag et al.Type=AT, Architecture=WideResNet-28-102023.07 | 90.93 | 83.75 | |
| Yoon et al.Type=AP, Architecture=WideResNet-70-162023.07 | 86.76 | 75.9 | |
| Yoon et al.Type=AP, Architecture=WideResNet-28-102023.07 | 85.66 | 74.26 |