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SOTA
Continual Learning
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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