Image Classification on OxfordPets 16-shot (Top-1 Clean and Robust Accuracy)
85.04Top-1 Clean AccuracyCLBP
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| CLBPPerturbation budget (epsilon)=1/255, Attack ensemble=APGD-CE + APGD-DLR2026.05 | 85.04 | 78.6 | |
| CLBPPerturbation budget (epsilon)=2/255, Attack ensemble=APGD-CE + APGD-DLR2026.05 | 85.04 | 75.2 | |
| CLBPPerturbation budget (epsilon)=4/255, Attack ensemble=APGD-CE + APGD-DLR2026.05 | 85.04 | 68.93 | |
| FAPPerturbation budget (epsilon)=1/255, Attack ensemble=APGD-CE + APGD-DLR2026.05 | 80.02 | 30.19 | |
| FAPPerturbation budget (epsilon)=2/255, Attack ensemble=APGD-CE + APGD-DLR2026.05 | 80.02 | 22.82 | |
| FAPPerturbation budget (epsilon)=4/255, Attack ensemble=APGD-CE + APGD-DLR2026.05 | 80.02 | 12.27 | |
| AdvVLPPerturbation budget (epsilon)=1/255, Attack ensemble=APGD-CE + APGD-DLR2026.05 | 79.18 | 26.4 | |
| AdvVLPPerturbation budget (epsilon)=2/255, Attack ensemble=APGD-CE + APGD-DLR2026.05 | 79.18 | 19.13 | |
| AdvVLPPerturbation budget (epsilon)=4/255, Attack ensemble=APGD-CE + APGD-DLR2026.05 | 79.18 | 9.26 | |
| AdvVPPerturbation budget (epsilon)=1/255, Attack ensemble=APGD-CE + APGD-DLR2026.05 | 78 | 17.32 | |
| AdvVPPerturbation budget (epsilon)=2/255, Attack ensemble=APGD-CE + APGD-DLR2026.05 | 78 | 3.98 | |
| AdvVPPerturbation budget (epsilon)=4/255, Attack ensemble=APGD-CE + APGD-DLR2026.05 | 78 | 0.34 | |
| AdvMaPLePerturbation budget (epsilon)=1/255, Attack ensemble=APGD-CE + APGD-DLR2026.05 | 78 | 26.24 | |
| AdvMaPLePerturbation budget (epsilon)=2/255, Attack ensemble=APGD-CE + APGD-DLR2026.05 | 78 | 19 | |
| AdvMaPLePerturbation budget (epsilon)=4/255, Attack ensemble=APGD-CE + APGD-DLR2026.05 | 78 | 9.48 |