Image Classification on Visual Decathlon UCF101 held-out target
50.82AccuracyFeature-Critic
Evaluation results
| Method | Links | |
|---|---|---|
| Feature-CriticClassifier=SVM, Backbone=ResNet-182019.01 | 50.82 | |
| ReptileClassifier=SVM, Backbone=ResNet-182019.01 | 49.85 | |
| MetaReg-FLClassifier=SVM, Backbone=ResNet-182019.01 | 48.1 | |
| MetaRegClassifier=SVM, Backbone=ResNet-182019.01 | 47.34 | |
| Data AggregationClassifier=SVM, Backbone=ResNet-182019.01 | 46.98 | |
| CrossGradClassifier=SVM, Backbone=ResNet-182019.01 | 45.8 | |
| ImageNet Pre-trainedClassifier=SVM, Backbone=ResNet-182019.01 | 44.93 | |
| Feature-CriticClassifier=KNN, Backbone=ResNet-182019.01 | 41.87 | |
| ReptileClassifier=KNN, Backbone=ResNet-182019.01 | 39.06 | |
| Data AggregationClassifier=KNN, Backbone=ResNet-182019.01 | 38.04 | |
| CrossGradClassifier=KNN, Backbone=ResNet-182019.01 | 37.95 | |
| ImageNet Pre-trainedClassifier=KNN, Backbone=ResNet-182019.01 | 35.25 | |
| MetaReg-FLClassifier=KNN, Backbone=ResNet-182019.01 | 35.25 | |
| MetaRegClassifier=KNN, Backbone=ResNet-182019.01 | 34.43 |