Image Classification on ImageNet100 Task 2(80-20) 1.0 (test)
90.63AccuracyDER++
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| DER++2026.01 | 90.63 | 84.13 | 11.1 | 50.1 | |
| DER2026.01 | 90.57 | 84.22 | 10.9 | 50.8 | |
| Pre-train2026.01 | 90.03 | — | 89.6 | — | |
| L2*2026.01 | 88.37 | 83.59 | 10.3 | 48.1 | |
| FG-OrIU2026.01 | 87.43 | 88.45 | 0.1 | 0.1 | |
| LwF2026.01 | 85.4 | 87.26 | 0.4 | 2.4 | |
| GS-LoRA2026.01 | 85.27 | 87.33 | 0.1 | 1.1 | |
| GS-LoRA++2026.01 | 85.23 | 87.22 | 0.3 | 0.3 | |
| EWC*2026.01 | 82.57 | 85.71 | 0.5 | 0.2 | |
| SCRUB-S2026.01 | 76.6 | 82.59 | 0 | 0.1 | |
| MAS*2026.01 | 74.77 | 81.51 | 0 | 0.6 | |
| LIRF*2026.01 | 69.83 | 61.05 | 35.36 | 32.15 | |
| BAD-T2026.01 | 69.21 | 78.09 | 0 | 0.1 | |
| SCRUB2026.01 | 66.33 | 76.23 | 0 | 0 | |
| Retrain2026.01 | 41.3 | 56.28 | 1.3 | 0 | |
| FDR2026.01 | 22.7 | 36.21 | 0.1 | 0 |