Unsupervised Few Shot Image Classification On 1
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | Accuracy |
|---|---|
| revisiting-unsupervised-meta-learning | 75.77 |
| unsupervised-meta-learning-via-latent-space | 58.03 |
| multi-level-second-order-few-shot-learning | 55.38 |
| contrastive-prototypical-network-with | 73.21 |
| self-supervision-can-be-a-good-few-shot | 83.40 |
| unsupervised-few-shot-image-classification-by | 67.36 |
| rethinking-class-relations-absolute-relative | 57.01 |
| trainable-class-prototypes-for-few-shot | 73.94 |
| shot-in-the-dark-few-shot-learning-with-no-1 | 77.2 |
| few-shot-image-classification-via-contrastive | 68.91 |
| unsupervised-meta-learning-for-few-shot-image | 50.73 |
| assume-augment-and-learn-unsupervised-few | 49.18 |
| self-attention-message-passing-for | 72.52 |
| meta-gmvae-mixture-of-gaussian-vae-for | 55.73 |
| self-supervised-class-cognizant-few-shot | 64.81 |
| cmvae-causal-meta-vae-for-unsupervised-meta | 58.95 |
| meta-dm-applications-of-diffusion-models-on | 85.29 |
| unsupervised-meta-learning-via-few-shot-1 | 63.26 |
| invariant-and-consistent-unsupervised | 56.96 |
| beclr-batch-enhanced-contrastive-few-shot | 87.82 |
| unsupervised-few-shot-learning-via-deep | 78.79 |
| self-supervised-learning-for-few-shot-image | 70.14 |
| unsupervised-few-shot-learning-via | 56.18 |
| unsupervised-meta-learning-through-latent | 54.56 |
| self-supervised-prototypical-transfer | 62.99 |
| rethinking-clustering-based-pseudo-labeling | 62.91 |
| unsupervised-learning-via-meta-learning | 53.97 |
| few-shot-learning-with-part-discovery-and | 83.11 |