Class-incremental Learning on Tiny ImageNet i-Blurry-50-10 (test)
53.05Average AccuracyStandard
Evaluation Results
| Method | Links | |
|---|---|---|
| Standard2025.07 | 53.05 | |
| EB (w/ DMA)Number of tasks (t)=5, Pre-trained initialization (PR)=ImageNet, i-Blurry setting (n/m)=50/102025.07 | 47.68 | |
| EB (w/o DMA)Number of tasks (t)=5, Pre-trained initialization (PR)=ImageNet, i-Blurry setting (n/m)=50/102025.07 | 40.21 | |
| FOSTERNumber of tasks (t)=5, Pre-trained initialization (PR)=ImageNet, i-Blurry setting (n/m)=50/102025.07 | 33.93 | |
| iCaRLNumber of tasks (t)=5, Pre-trained initialization (PR)=ImageNet, i-Blurry setting (n/m)=50/102025.07 | 25.41 | |
| CLIBNumber of tasks (t)=5, Pre-trained initialization (PR)=ImageNet, i-Blurry setting (n/m)=50/102025.07 | 25.05 | |
| BiCNumber of tasks (t)=5, Pre-trained initialization (PR)=ImageNet, i-Blurry setting (n/m)=50/102025.07 | 24.9 | |
| FTFNumber of tasks (t)=5, Pre-trained initialization (PR)=ImageNet, i-Blurry setting (n/m)=50/102025.07 | 24.58 | |
| ER-MIRNumber of tasks (t)=5, Pre-trained initialization (PR)=ImageNet, i-Blurry setting (n/m)=50/102025.07 | 24.54 | |
| EWC++Number of tasks (t)=5, Pre-trained initialization (PR)=ImageNet, i-Blurry setting (n/m)=50/102025.07 | 24.39 | |
| GDumbNumber of tasks (t)=5, Pre-trained initialization (PR)=ImageNet, i-Blurry setting (n/m)=50/102025.07 | 18.69 | |
| RMNumber of tasks (t)=5, Pre-trained initialization (PR)=ImageNet, i-Blurry setting (n/m)=50/102025.07 | 17.04 |