Exemplar-Free Class-Incremental Learning on CIFAR-100 10-Tasks
26.53Average Accuracy (AA)Inf-SSM
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| Inf-SSMBackbone=Vim-Small, Regularization focus=geometry-aware2025.05 | 26.53 | 54.24 | 24 | |
| Inf-SSMBackbone=Vim-small2025.05 | 26.53 | 54.24 | 24 | |
| LwF-ABCBackbone=Vim-Small, Regularization focus=(A, B, C)2025.05 | 24.39 | 53.48 | 25.29 | |
| LwF-ABCBackbone=Vim-small2025.05 | 24.39 | 53.48 | 25.29 | |
| EWCBackbone=Vim-Small, Regularization focus=(A, B, C)2025.05 | 22.2 | 53.46 | 63.92 | |
| EwCBackbone=Vim-small2025.05 | 22.2 | 53.46 | 63.92 | |
| UCLBackbone=Vim-small2025.05 | 21.71 | 50.35 | 29.16 | |
| SeqBackbone=Vim-Small, Regularization focus=(A, B, C)2025.05 | 20.58 | 51.37 | 71.49 | |
| SeqBackbone=Vim-small2025.05 | 20.58 | 51.37 | 71.49 | |
| MASBackbone=Vim-Small, Regularization focus=(A, B, C)2025.05 | 20.44 | 49.69 | 37.99 | |
| MASBackbone=Vim-small2025.05 | 20.44 | 49.69 | 37.99 | |
| SIBackbone=Vim-Small, Regularization focus=(A, B, C)2025.05 | 20.29 | 49.28 | 38.33 | |
| SIBackbone=Vim-small2025.05 | 20.29 | 49.28 | 38.33 |