| RIDE-DiVE |
- Top-1 Accuracy
- 57.12
|
Distilling Virtual Examples for Long-tailed Recognition 2021-03-28 |
코드 1 |
| BCL(ResNeXt-50) |
- Top-1 Accuracy
- 57.1
|
Balanced Contrastive Learning for Long-Tailed Visual Recognition 2022-07-19 |
코드 1 |
| RIDE (ResNeXt-50) |
- Top-1 Accuracy
- 56.4
|
Long-tailed Recognition by Routing Diverse Distribution-Aware Experts 2020-10-05 |
코드 1 · 코드 2 |
| GLMC (ResNeXt-50) |
- Top-1 Accuracy
- 56.3
|
Global and Local Mixture Consistency Cumulative Learning for Long-tailed Visual Recognitions 2023-05-15 |
코드 1 · 코드 2 |
| BatchFormer(ResNet-50, RIDE) |
- Top-1 Accuracy
- 55.7
|
BatchFormer: Learning to Explore Sample Relationships for Robust Representation Learning 2022-03-03 |
코드 1 |
| CBD-ENS (ResNet-50) |
- Top-1 Accuracy
- 55.6
|
Class-Balanced Distillation for Long-Tailed Visual Recognition 2021-04-12 |
코드 1 · 코드 2 · 코드 3 |
| ResLT(ResNeXt101-32x4d) |
- Top-1 Accuracy
- 55.1
|
ResLT: Residual Learning for Long-tailed Recognition 2021-01-26 |
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 |
| OPeN (ResNeXt-50) |
- Top-1 Accuracy
- 55.1
|
Pure Noise to the Rescue of Insufficient Data: Improving Imbalanced Classification by Training on Random Noise Images 2021-12-16 |
코드 1 |
| RIDE (ResNet-50) |
- Top-1 Accuracy
- 54.9
|
Long-tailed Recognition by Routing Diverse Distribution-Aware Experts 2020-10-05 |
코드 1 · 코드 2 |
| Difficulty-Net (ResNet-50 w/o using RandAugment, single model) |
- Top-1 Accuracy
- 54.0
|
Difficulty-Net: Learning to Predict Difficulty for Long-Tailed Recognition 2022-09-07 |
코드 1 |
| LTR-weight-balancing(ResNeXt-50) |
- Top-1 Accuracy
- 53.9
|
Long-Tailed Recognition via Weight Balancing 2022-03-27 |
코드 1 · 코드 2 |
| DRO-LT |
- Top-1 Accuracy
- 53.5
|
Distributional Robustness Loss for Long-tail Learning 2021-04-07 |
연결 없음 |
| DisAlign |
- Top-1 Accuracy
- 53.4
|
Distribution Alignment: A Unified Framework for Long-tail Visual Recognition 2021-03-30 |
코드 1 |
| DiVE |
- Top-1 Accuracy
- 53.1
|
Distilling Virtual Examples for Long-tailed Recognition 2021-03-28 |
코드 1 |
| LDAM + DRW + SAM |
- Top-1 Accuracy
- 53.1
|
Escaping Saddle Points for Effective Generalization on Class-Imbalanced Data 2022-12-28 |
코드 1 |
| LADE |
- Top-1 Accuracy
- 53.0
|
Disentangling Label Distribution for Long-tailed Visual Recognition 2020-12-01 |
코드 1 · 코드 2 |
| ResLT(ResNeXt50) |
- Top-1 Accuracy
- 52.9
|
ResLT: Residual Learning for Long-tailed Recognition 2021-01-26 |
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 |
| MiSLAS |
- Top-1 Accuracy
- 52.7
|
Improving Calibration for Long-Tailed Recognition 2021-04-01 |
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 |
| TSC(ResNet-50) |
- Top-1 Accuracy
- 52.4
|
Targeted Supervised Contrastive Learning for Long-Tailed Recognition 2021-11-27 |
코드 1 |
| LDAM-DRS-RSG |
- Top-1 Accuracy
- 51.8
|
RSG: A Simple but Effective Module for Learning Imbalanced Datasets 2021-06-18 |
코드 1 |
| De-confound-TDE |
- Top-1 Accuracy
- 51.8
|
Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect 2020-09-28 |
코드 1 · 코드 2 |
| KCL |
- Top-1 Accuracy
- 51.5
|
Exploring Balanced Feature Spaces for Representation Learning 2021-01-01 |
연결 없음 |
| cRT + SSP |
- Top-1 Accuracy
- 51.3
|
Rethinking the Value of Labels for Improving Class-Imbalanced Learning 2020-06-13 |
코드 1 |
| Logit adjustment |
- Top-1 Accuracy
- 51.3
|
Long-tail learning via logit adjustment 2020-07-14 |
코드 1 · 코드 2 · 코드 3 |
| MetaSAug (ResNet-152) |
- Top-1 Accuracy
- 50.03
|
MetaSAug: Meta Semantic Augmentation for Long-Tailed Visual Recognition 2021-03-23 |
코드 1 |
| MetaSAug with CE loss |
- Top-1 Accuracy
- 47.39
|
MetaSAug: Meta Semantic Augmentation for Long-Tailed Visual Recognition 2021-03-23 |
코드 1 |
| BLT (DenseNet-121) |
- Top-1 Accuracy
- 44.7
|
BLT: Balancing Long-Tailed Datasets with Adversarially-Perturbed Images 2020-10-30 |
코드 1 |
| Difficulty-Net (ResNet-10 w/o using RandAugment, single model |
- Top-1 Accuracy
- 44.6
|
Difficulty-Net: Learning to Predict Difficulty for Long-Tailed Recognition 2022-09-07 |
코드 1 |
| IEM |
- Top-1 Accuracy
- 43.2
|
Inflated Episodic Memory With Region Self-Attention for Long-Tailed Visual Recognition 2020-06-01 |
연결 없음 |
| smDRAGON |
- Top-1 Accuracy
- 42.0
|
From Generalized zero-shot learning to long-tail with class descriptors 2020-04-05 |
코드 1 |