| BECLR |
- Accuracy
- 87.82
|
BECLR: Batch Enhanced Contrastive Few-Shot Learning 2024-02-04 |
코드 1 |
| Meta-DM+UniSiam |
- Accuracy
- 85.29
|
Meta-DM: Applications of Diffusion Models on Few-Shot Learning 2023-05-14 |
연결 없음 |
| UniSiam |
- Accuracy
- 83.40
|
Self-Supervision Can Be a Good Few-Shot Learner 2022-07-19 |
코드 1 · 코드 2 · 코드 3 · 코드 4 |
| PDA-Net |
- Accuracy
- 83.11
|
Few-Shot Learning with Part Discovery and Augmentation from Unlabeled Images 2021-05-25 |
연결 없음 |
| Deep Laplacian Eigenmaps |
- Accuracy
- 78.79
|
Unsupervised Few-shot Learning via Deep Laplacian Eigenmaps 2022-10-07 |
연결 없음 |
| UBC-FSL |
- Accuracy
- 77.2
|
Shot in the Dark: Few-Shot Learning with No Base-Class Labels 2020-10-06 |
연결 없음 |
| HMS |
- Accuracy
- 75.77
|
Revisiting Unsupervised Meta-Learning via the Characteristics of Few-Shot Tasks 2020-11-30 |
코드 1 |
| TrainProto |
- Accuracy
- 73.94
|
Trainable Class Prototypes for Few-Shot Learning 2021-06-21 |
연결 없음 |
| CPNWCP |
- Accuracy
- 73.21
|
Contrastive Prototypical Network with Wasserstein Confidence Penalty 2022-10-21 |
코드 1 |
| SAMPTransfer (Conv4) |
- Accuracy
- 72.52
|
Self-Attention Message Passing for Contrastive Few-Shot Learning 2022-10-12 |
코드 1 |
| AmdimNet |
- Accuracy
- 70.14
|
Self-Supervised Learning For Few-Shot Image Classification 2019-11-14 |
코드 1 · 코드 2 |
| CSSL |
- Accuracy
- 68.91
|
Few-Shot Image Classification via Contrastive Self-Supervised Learning 2020-08-23 |
연결 없음 |
| LF2CS |
- Accuracy
- 67.36
|
Unsupervised Few-Shot Image Classification by Learning Features into Clustering Space 2022-10-21 |
코드 1 |
| C^3LR |
- Accuracy
- 64.81
|
Self-Supervised Class-Cognizant Few-Shot Classification 2022-02-15 |
코드 1 |
| PsCo |
- Accuracy
- 63.26
|
Unsupervised Meta-Learning via Few-shot Pseudo-supervised Contrastive Learning 2023-03-02 |
코드 1 |
| ProtoTransfer |
- Accuracy
- 62.99
|
Self-Supervised Prototypical Transfer Learning for Few-Shot Classification 2020-06-19 |
코드 1 · 코드 2 |
| PL-CFE |
- Accuracy
- 62.91
|
Rethinking Clustering-Based Pseudo-Labeling for Unsupervised Meta-Learning 2022-09-27 |
코드 1 |
| CMVAE |
- Accuracy
- 58.95
|
CMVAE: Causal Meta VAE for Unsupervised Meta-Learning 2023-02-20 |
코드 1 |
| Meta-SVEBM |
- Accuracy
- 58.03
|
Unsupervised Meta-Learning via Latent Space Energy-based Model of Symbol Vector Coupling 2021-09-30 |
연결 없음 |
| ArL |
- Accuracy
- 57.01
|
Rethinking Class Relations: Absolute-relative Supervised and Unsupervised Few-shot Learning 2020-01-12 |
코드 1 |
| InCo |
- Accuracy
- 56.96
|
Invariant and consistent: Unsupervised representation learning for few-shot visual recognition 2022-11-01 |
연결 없음 |
| ULDA |
- Accuracy
- 56.18
|
Diversity Helps: Unsupervised Few-shot Learning via Distribution Shift-based Data Augmentation 2020-04-13 |
코드 1 |
| Meta-GMVAE |
- Accuracy
- 55.73
|
Meta-GMVAE: Mixture of Gaussian VAE for Unsupervised Meta-Learning 2021-01-01 |
코드 1 |
| U-MlSo+PN |
- Accuracy
- 55.38
|
Multi-level Second-order Few-shot Learning 2022-01-15 |
코드 1 |
| LASIUM |
- Accuracy
- 54.56
|
Unsupervised Meta-Learning through Latent-Space Interpolation in Generative Models 2020-06-18 |
연결 없음 |
| CACTU |
- Accuracy
- 53.97
|
Unsupervised Learning via Meta-Learning 2018-10-04 |
연결 없음 |
| UMTRA |
- Accuracy
- 50.73
|
Unsupervised Meta-Learning For Few-Shot Image Classification 2018-11-28 |
연결 없음 |
| AAL |
- Accuracy
- 49.18
|
Assume, Augment and Learn: Unsupervised Few-Shot Meta-Learning via Random Labels and Data Augmentation 2019-02-26 |
연결 없음 |