Image Classification on TinyImageNet 200 (Surrogate Model Accuracy)
90.88Surrogate Model AccuracyNo-Shield
Evaluation results
| Method | Links | |
|---|---|---|
| No-ShieldBackbone=ViT-Base2026.03 | 90.88 | |
| MagnitudeBackbone=ViT-Base2026.03 | 88.14 | |
| SerdabBackbone=ViT-Base2026.03 | 86.1 | |
| DarkneTZBackbone=ViT-Base2026.03 | 79.08 | |
| No-ShieldBackbone=VGG16-BN2026.03 | 62.14 | |
| SerdabBackbone=VGG16-BN2026.03 | 62.07 | |
| No-ShieldBackbone=ResNet-182026.03 | 61.28 | |
| MagnitudeBackbone=VGG16-BN2026.03 | 60.35 | |
| SerdabBackbone=ResNet-182026.03 | 58.33 | |
| MagnitudeBackbone=ResNet-182026.03 | 54.05 | |
| TEESliceBackbone=ViT-Base2026.03 | 45.23 | |
| Black-boxBackbone=ViT-Base2026.03 | 43.65 | |
| DarkneTZBackbone=VGG16-BN2026.03 | 37.06 | |
| DarkneTZBackbone=ResNet-182026.03 | 27.78 | |
| Black-boxBackbone=VGG16-BN2026.03 | 25.52 | |
| TEESliceBackbone=VGG16-BN2026.03 | 25.14 | |
| TEESliceBackbone=ResNet-182026.03 | 15.51 | |
| Black-boxBackbone=ResNet-182026.03 | 14.42 | |
| TB-NetBackbone=VGG16-BN2026.03 | 3.73 | |
| GroupCoverBackbone=ResNet-182026.03 | 3.3 | |
| GroupCoverBackbone=VGG16-BN2026.03 | 2.04 | |
| TB-NetBackbone=ResNet-182026.03 | 2.01 | |
| SPOILERBackbone=ResNet-182026.03 | 1.55 | |
| SPOILERBackbone=VGG16-BN2026.03 | 0.71 | |
| SPOILERBackbone=ViT-Base2026.03 | 0.53 | |
| GroupCoverBackbone=ViT-Base2026.03 | 0.5 |