| PrototypeCompletion |
- Accuracy
- 84.18
|
Prototype Completion for Few-Shot Learning 2021-08-11 |
코드 1 |
| ESPT |
- Accuracy
- 84.11
|
ESPT: A Self-Supervised Episodic Spatial Pretext Task for Improving Few-Shot Learning 2023-04-26 |
코드 1 |
| DAPNA |
- Accuracy
- 84.07
|
Few-Shot Learning as Domain Adaptation: Algorithm and Analysis 2020-02-06 |
연결 없음 |
| SKD |
- Accuracy
- 83.54
|
Self-supervised Knowledge Distillation for Few-shot Learning 2020-06-17 |
코드 1 · 코드 2 |
| UniSiam |
- Accuracy
- 83.40
|
Self-Supervision Can Be a Good Few-Shot Learner 2022-07-19 |
코드 1 · 코드 2 · 코드 3 · 코드 4 |
| OSLO |
- Accuracy
- 83.4
|
Open-Set Likelihood Maximization for Few-Shot Learning 2023-01-20 |
코드 1 |
| S2M2R |
- Accuracy
- 83.18
|
Charting the Right Manifold: Manifold Mixup for Few-shot Learning 2019-07-28 |
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 · 코드 7 · 코드 8 |
| SSFormers |
- Accuracy
- 82.75
|
Sparse Spatial Transformers for Few-Shot Learning 2021-09-27 |
코드 1 |
| RENet |
- Accuracy
- 82.58
|
Relational Embedding for Few-Shot Classification 2021-08-22 |
코드 1 |
| pseudo-shots |
- Accuracy
- 82.51
|
Extended Few-Shot Learning: Exploiting Existing Resources for Novel Tasks 2020-12-13 |
코드 1 · 코드 2 |
| BD-CSPN + ESFR (ResNet-18) |
- Accuracy
- 82.32
|
Unsupervised Embedding Adaptation via Early-Stage Feature Reconstruction for Few-Shot Classification 2021-06-22 |
코드 1 |
| WRN + Self-Organizing Map |
- Accuracy
- 82.2
|
GPU-based Self-Organizing Maps for Post-Labeled Few-Shot Unsupervised Learning 2020-09-04 |
코드 1 |
| MetaOptNet-SVM+Task Aug |
- Accuracy
- 82.13
|
Task Augmentation by Rotating for Meta-Learning 2020-02-08 |
코드 1 |
| R2-D2+Task Aug |
- Accuracy
- 81.96
|
Task Augmentation by Rotating for Meta-Learning 2020-02-08 |
코드 1 |
| Adaptive Subspace Network |
- Accuracy
- 81.65
|
Adaptive Subspaces for Few-Shot Learning 2020-06-01 |
코드 1 |
| SimpleShot (CL2N-DenseNet) |
- Accuracy
- 81.5
|
SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning 2019-11-12 |
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 |
| GML (ResNet-12) |
- Accuracy
- 81.13
|
Geometric Mean Improves Loss For Few-Shot Learning 2025-01-24 |
연결 없음 |
| MetaFun-Attention |
- Accuracy
- 80.82
|
MetaFun: Meta-Learning with Iterative Functional Updates 2019-12-05 |
코드 1 |
| DiffKendall (Meta-Baseline, ResNet-12) |
- Accuracy
- 80.79
|
DiffKendall: A Novel Approach for Few-Shot Learning with Differentiable Kendall's Rank Correlation 2023-07-28 |
코드 1 |
| ACC + Amphibian |
- Accuracy
- 80.75
|
Generalized Adaptation for Few-Shot Learning 2019-11-25 |
연결 없음 |
| MergedNet-Max |
- Accuracy
- 80.40
|
MergedNET: A simple approach for one-shot learning in siamese networks based on similarity layers 2022-10-14 |
코드 1 |
| MCRNet-SVM |
- Accuracy
- 80.34
|
Complementing Representation Deficiency in Few-shot Image Classification: A Meta-Learning Approach 2020-07-21 |
코드 1 |
| ICI |
- Accuracy
- 80.11
|
Instance Credibility Inference for Few-Shot Learning 2020-03-26 |
코드 1 |
| MetaOptNet-SVM-trainval |
- Accuracy
- 80
|
Meta-Learning with Differentiable Convex Optimization 2019-04-07 |
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 · 코드 7 |
| ConstellationNets |
- Accuracy
- 79.95
|
Constellation Nets for Few-Shot Learning 2021-01-01 |
코드 1 |
| TRAML |
- Accuracy
- 79.54
|
Boosting Few-Shot Learning With Adaptive Margin Loss 2020-05-28 |
연결 없음 |
| SIB |
- Accuracy
- 79.2
|
Empirical Bayes Transductive Meta-Learning with Synthetic Gradients 2020-04-27 |
코드 1 · 코드 2 |
| LST |
- Accuracy
- 78.7
|
Learning to Self-Train for Semi-Supervised Few-Shot Classification 2019-06-03 |
코드 1 |
| feat+ (ProtoNet-ResNet) |
- Accuracy
- 78.38
|
Few-Shot Learning via Embedding Adaptation with Set-to-Set Functions 2018-12-10 |
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 |
| MCRNet-RR |
- Accuracy
- 78.16
|
Complementing Representation Deficiency in Few-shot Image Classification: A Meta-Learning Approach 2020-07-21 |
코드 1 |