Unsupervised Few Shot Image Classification On
評価指標
Accuracy
評価結果
このベンチマークにおける各モデルのパフォーマンス結果
比較表
| モデル名 | Accuracy |
|---|---|
| unsupervised-meta-learning-via-few-shot-1 | 46.70 |
| shot-in-the-dark-few-shot-learning-with-no-1 | 57.1 |
| beclr-batch-enhanced-contrastive-few-shot | 80.57 |
| self-supervision-can-be-a-good-few-shot | 65.55 |
| contrastive-prototypical-network-with | 53.56 |
| rethinking-class-relations-absolute-relative | 41.08 |
| unsupervised-few-shot-learning-via-deep | 59.47 |
| revisiting-unsupervised-meta-learning | 58.20 |
| few-shot-image-classification-via-contrastive | 54.17 |
| unsupervised-few-shot-learning-via | 40.71 |
| assume-augment-and-learn-unsupervised-few | 37.67 |
| self-supervised-learning-for-few-shot-image | 46.13 |
| multi-level-second-order-few-shot-learning | 41.09 |
| trainable-class-prototypes-for-few-shot | 58.92 |
| unsupervised-few-shot-image-classification-by | 53.14 |
| unsupervised-meta-learning-for-few-shot-image | 39.93 |
| unsupervised-learning-via-meta-learning | 39.90 |
| meta-dm-applications-of-diffusion-models-on | 66.68 |
| self-supervised-prototypical-transfer | 45.67 |
| self-supervised-class-cognizant-few-shot | 47.92 |
| rethinking-clustering-based-pseudo-labeling | 49.13 |
| cmvae-causal-meta-vae-for-unsupervised-meta | 44.27 |
| few-shot-learning-with-part-discovery-and | 63.84 |
| meta-gmvae-mixture-of-gaussian-vae-for | 42.82 |
| self-attention-message-passing-for | 61.02 |
| invariant-and-consistent-unsupervised | 41.44 |
| unsupervised-meta-learning-through-latent | 40.05 |
| unsupervised-meta-learning-via-latent-space | 43.38 |