Image Classification on ImageNet100 Task 3(60-20) 1.0 (test)
91.3AccuracyDER++
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| DER++2026.01 | 91.3 | 87.5 | 6.8 | 40.4 | |
| DER2026.01 | 91.2 | 86.36 | 8.8 | 42 | |
| Pre-train2026.01 | 89.65 | — | 90.8 | — | |
| L2*2026.01 | 88.2 | 84.01 | 10.6 | 37.15 | |
| FG-OrIU2026.01 | 87.35 | 88.9 | 0.3 | 0 | |
| GS-LoRA2026.01 | 85.15 | 87.84 | 0.1 | 0.35 | |
| EWC*2026.01 | 84.9 | 87.33 | 0.9 | 2.9 | |
| GS-LoRA++2026.01 | 84.4 | 87.48 | 0 | 0.6 | |
| LwF2026.01 | 84.15 | 87.35 | 0 | 2.35 | |
| MAS*2026.01 | 75.05 | 82.18 | 0 | 0.6 | |
| SCRUB-S2026.01 | 71.2 | 79.81 | 0 | 0 | |
| BAD-T2026.01 | 66.32 | 76.65 | 0 | 0 | |
| SCRUB2026.01 | 64.55 | 75.46 | 0 | 0 | |
| LIRF*2026.01 | 60.32 | 60.96 | 29.18 | 30.91 | |
| Retrain2026.01 | 47.55 | 61.14 | 5.2 | 0.2 | |
| FDR2026.01 | 26.3 | 40.79 | 0 | 0 |