Exemplar-Free Class-Incremental Learning on CIFAR-100 5-Tasks
45.18AAInf-SSM
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| Inf-SSMBackbone=Vim-Small, Regularization focus=geometry-aware2025.05 | 45.18 | 67.34 | 36.59 | |
| Inf-SSMBackbone=Vim-small2025.05 | 45.18 | 67.34 | 36.59 | |
| LwF-ABCBackbone=Vim-Small, Regularization focus=(A, B, C)2025.05 | 44.62 | 66.81 | 38.68 | |
| LwF-ABCBackbone=Vim-small2025.05 | 44.62 | 66.81 | 38.68 | |
| UCLBackbone=Vim-small2025.05 | 39.48 | 62.62 | 46.52 | |
| EWCBackbone=Vim-Small, Regularization focus=(A, B, C)2025.05 | 38.25 | 63.12 | 50.71 | |
| EWCBackbone=Vim-small2025.05 | 38.25 | 63.12 | 50.71 | |
| MASBackbone=Vim-Small, Regularization focus=(A, B, C)2025.05 | 37.59 | 61.95 | 53.13 | |
| MASBackbone=Vim-small2025.05 | 37.59 | 61.95 | 53.13 | |
| SIBackbone=Vim-Small, Regularization focus=(A, B, C)2025.05 | 37.38 | 61.78 | 53.04 | |
| SIBackbone=Vim-small2025.05 | 37.38 | 61.78 | 53.04 | |
| SeqBackbone=Vim-Small, Regularization focus=(A, B, C)2025.05 | 36.68 | 61.25 | 55 | |
| SeqBackbone=Vim-small2025.05 | 36.68 | 61.25 | 55 |