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SotA/Methodology/Continual Learning/visual domain decathlon (10 tasks)

Continual Learning on visual domain decathlon (10 tasks)

Metric: decathlon discipline (Score) (higher is better)

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#Model↕decathlon discipline (Score)▼AugmentationsPaperDate↕Code
1NetTailor3744NoNetTailor: Tuning the Architecture, Not Just the...2019-06-29Code
2Depthwise Soft Sharing3507NoDepthwise Convolution is All You Need for Learni...2019-02-03Code
3Parallel Res. adapt.3412NoEfficient parametrization of multi-domain deep n...2018-03-27Code
4Depthwise Sharing3234NoDepthwise Convolution is All You Need for Learni...2019-02-03Code
5Series Res. adapt.3159NoEfficient parametrization of multi-domain deep n...2018-03-27Code
6Res. adapt. (large)3131NoLearning multiple visual domains with residual a...2017-05-22Code
7DAN2851NoIncremental Learning Through Deep Adaptation2017-05-11-
8Piggyback2838NoPiggyback: Adapting a Single Network to Multiple...2018-01-19Code
9Res. adapt. finetune all2643NoLearning multiple visual domains with residual a...2017-05-22Code
10Res. adapt. decay2621NoLearning multiple visual domains with residual a...2017-05-22Code
11LwF2515NoLearning without Forgetting2016-06-29Code
12Res. adapt. dom-pred2503NoLearning multiple visual domains with residual a...2017-05-22Code
13Res. adapt.2118NoLearning multiple visual domains with residual a...2017-05-22Code
14BN adapt.1363NoUniversal representations:The missing link betwe...2017-01-25-