Few Shot Image Classification On Dirichlet 1
Metrics
1:1 Accuracy
Results
Performance results of various models on this benchmark
Model Name | 1:1 Accuracy | Paper Title | Repository |
|---|---|---|---|
| LR-ICI | 73.5 | Instance Credibility Inference for Few-Shot Learning | |
| alpha-TIM | 82.5 | Realistic Evaluation of Transductive Few-Shot Learning | |
| BDCSPN | 80.2 | Prototype Rectification for Few-Shot Learning | |
| MAML | 64.5 | Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks | |
| Versa | 61.9 | Meta-Learning Probabilistic Inference For Prediction | |
| Simpleshot | 80.1 | SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning | - |
| Entropy Minimization | 74.8 | A Baseline for Few-Shot Image Classification | |
| ProtoNet | 74.2 | Prototypical Networks for Few-shot Learning | |
| BAVARDAGE | 83.6 | Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification | - |
| Baseline++ | 79.7 | A Closer Look at Few-shot Classification | |
| PT-MAP | 67.1 | Leveraging the Feature Distribution in Transfer-based Few-Shot Learning | |
| Laplacian-Shot | 81.6 | Laplacian Regularized Few-Shot Learning |
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