Continual Learning On Wikiart Fine Grained 6
Métriques
Accuracy
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | Accuracy | Paper Title | Repository |
|---|---|---|---|
| ProgressiveNet | 74.94 | Progressive Neural Networks | |
| CPG | 77.15 | Compacting, Picking and Growing for Unforgetting Continual Learning | |
| H$^{2}$ | 75.1 | Helpful or Harmful: Inter-Task Association in Continual Learning | |
| CondConvContinual | 78.32 | EXTENDING CONDITIONAL CONVOLUTION STRUCTURES FOR ENHANCING MULTITASKING CONTINUAL LEARNING | |
| Piggyback | 71.33 | Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights | |
| PackNet | 69.40 | PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning |
0 of 6 row(s) selected.