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SOTA
Apprentissage continu
Continual Learning On Visual Domain Decathlon
Continual Learning On Visual Domain Decathlon
Métriques
decathlon discipline (Score)
Résultats
Résultats de performance de divers modèles sur ce benchmark
Columns
Nom du modèle
decathlon discipline (Score)
Paper Title
Repository
Res. adapt. finetune all
2643
Learning multiple visual domains with residual adapters
-
Piggyback
2838
Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights
-
Res. adapt.
2118
Learning multiple visual domains with residual adapters
-
DAN
2851
Incremental Learning Through Deep Adaptation
-
Res. adapt. decay
2621
Learning multiple visual domains with residual adapters
-
NetTailor
3744
NetTailor: Tuning the Architecture, Not Just the Weights
-
Res. adapt. dom-pred
2503
Learning multiple visual domains with residual adapters
-
Series Res. adapt.
3159
Efficient parametrization of multi-domain deep neural networks
-
LwF
2515
Learning without Forgetting
-
BN adapt.
1363
Universal representations:The missing link between faces, text, planktons, and cat breeds
-
Res. adapt. (large)
3131
Learning multiple visual domains with residual adapters
-
Depthwise Sharing
3234
Depthwise Convolution is All You Need for Learning Multiple Visual Domains
-
Depthwise Soft Sharing
3507
Depthwise Convolution is All You Need for Learning Multiple Visual Domains
-
Parallel Res. adapt.
3412
Efficient parametrization of multi-domain deep neural networks
-
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Continual Learning On Visual Domain Decathlon | SOTA | HyperAI