Image Classification on ImageNet100 Task 4(40-20) 1.0 (test)
94.8AccuracyDER++
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| DER++2026.01 | 94.8 | 89.24 | 2.2 | 20.8 | |
| DER2026.01 | 94.7 | 88.52 | 3.4 | 24.9 | |
| Pre-train2026.01 | 92.8 | — | 86.5 | — | |
| FG-OrIU2026.01 | 92.1 | 89.15 | 0.1 | 0 | |
| L2*2026.01 | 89.9 | 82.72 | 9.9 | 20.97 | |
| EWC*2026.01 | 89.5 | 86.93 | 2 | 8.27 | |
| GS-LoRA++2026.01 | 87.5 | 87 | 0 | 0.07 | |
| GS-LoRA2026.01 | 86.3 | 86.3 | 0.2 | 0.07 | |
| LwF2026.01 | 85.7 | 86.05 | 0.1 | 1.07 | |
| MAS*2026.01 | 77.9 | 81.93 | 0.1 | 1.77 | |
| SCRUB-S2026.01 | 71.4 | 78.23 | 0 | 0.07 | |
| SCRUB2026.01 | 70.3 | 77.56 | 0 | 0 | |
| LIRF*2026.01 | 68.46 | 58.51 | 35.41 | 21.04 | |
| BAD-T2026.01 | 68.17 | 76.25 | 0 | 0 | |
| Retrain2026.01 | 60.6 | 67.23 | 11 | 0.53 | |
| FDR2026.01 | 33.5 | 47.91 | 2.4 | 1.27 |