Continual Learning On Wikiart Fine Grained 6
Métriques
Accuracy
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | Accuracy |
|---|---|
| progressive-neural-networks | 74.94 |
| compacting-picking-and-growing-for | 77.15 |
| helpful-or-harmful-inter-task-association-in | 75.1 |
| extending-conditional-convolution-structures | 78.32 |
| piggyback-adapting-a-single-network-to | 71.33 |
| packnet-adding-multiple-tasks-to-a-single | 69.40 |