Few Shot Image Classification On Dirichlet 3
Metrics
1:1 Accuracy
Results
Performance results of various models on this benchmark
Model Name | 1:1 Accuracy | Paper Title | Repository |
|---|---|---|---|
| Simpleshot | 84.7 | SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning | - |
| Baseline++ | 84.2 | A Closer Look at Few-shot Classification | |
| alpha-TIM | 86.6 | Realistic Evaluation of Transductive Few-Shot Learning | |
| Entropy Minimization | 75.5 | A Baseline for Few-Shot Image Classification | |
| Laplacian-Shot | 85.7 | Laplacian Regularized Few-Shot Learning | |
| BDCSPN | 84.8 | Prototype Rectification for Few-Shot Learning | |
| LR+ICI | 85.1 | Instance Credibility Inference for Few-Shot Learning | |
| BAVARDAGE | 86.5 | Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification | - |
| PT-MAP | 70.0 | Leveraging the Feature Distribution in Transfer-based Few-Shot Learning |
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