Few Shot Image Classification On Dirichlet
Métriques
1:1 Accuracy
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | 1:1 Accuracy | Paper Title | Repository |
|---|---|---|---|
| MAML | 47.6 | Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks | |
| PT-MAP | 60.6 | Leveraging the Feature Distribution in Transfer-based Few-Shot Learning | |
| Versa | 47.8 | Meta-Learning Probabilistic Inference For Prediction | |
| BAVARDAGE | 71.0 | Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification | - |
| Laplacian-Shot | 65.4 | Laplacian Regularized Few-Shot Learning | |
| ProtoNet | 53.6 | Prototypical Networks for Few-shot Learning | |
| BD-CSPN | 67.0 | Prototype Rectification for Few-Shot Learning | |
| LR-ICI | 58.7 | Instance Credibility Inference for Few-Shot Learning | |
| alpha-TIM | 67.4 | Realistic Evaluation of Transductive Few-Shot Learning | |
| Entropy Minimization | 58.5 | A Baseline for Few-Shot Image Classification | |
| Simpleshot | 63.0 | SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning | - |
| Baseline ++ | 60.4 | A Closer Look at Few-shot Classification |
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