| Global and Local Mixture Consistency Cumulative Learning for Long-tailed Visual Recognitions | ✓ Link | 5 | GLMC+MaxNorm (ResNet-34, channel x4) | 2023-05-15 |
| SURE: SUrvey REcipes for building reliable and robust deep networks | ✓ Link | 5.04 | SURE(ResNet-32) | 2024-03-01 |
| Global and Local Mixture Consistency Cumulative Learning for Long-tailed Visual Recognitions | ✓ Link | 5.15 | GLMC (ResNet-34, channel x4) | 2023-05-15 |
| Delving Deep into Simplicity Bias for Long-Tailed Image Recognition | | 7.9 | 3LSSL | 2023-02-07 |
| Rebalanced Siamese Contrastive Mining for Long-Tailed Recognition | ✓ Link | 8.0 | ResCom | 2022-03-22 |
| A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning. paper with code | ✓ Link | 8.18 | VS + ADRW + TLA | 2023-10-07 |
| Balanced Meta-Softmax for Long-Tailed Visual Recognition | ✓ Link | 8.7 | Balanced Softmax (BALMS) | 2020-07-21 |
| Learning Imbalanced Data with Vision Transformers | ✓ Link | 8.7 | ViT-B + Bal-BCE | 2022-12-05 |
| Long-tailed Recognition by Learning from Latent Categories | | 8.8 | LCReg | 2022-06-02 |
| Balanced Contrastive Learning for Long-Tailed Visual Recognition | ✓ Link | 8.9 | BCL(ResNet-32) | 2022-07-19 |
| Contrastive Learning based Hybrid Networks for Long-Tailed Image Classification | | 8.9 | Hybrid-SC | 2021-03-26 |
| Decoupling Representation and Classifier for Long-Tailed Recognition | ✓ Link | 8.9 | LWS | 2019-10-21 |
| Decoupling Representation and Classifier for Long-Tailed Recognition | ✓ Link | 9.0 | cRT | 2019-10-21 |
| Parametric Contrastive Learning | ✓ Link | 9.14 | PCL | 2021-07-26 |
| Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition | ✓ Link | 9.2 | TADE | 2021-07-20 |
| Learning Imbalanced Data with Vision Transformers | ✓ Link | 9.3 | ViT-B + Bal-CE | 2022-12-05 |
| Equalization Loss for Long-Tailed Object Recognition | ✓ Link | 9.8 | Equalization Loss | 2020-03-11 |
| Improving Calibration for Long-Tailed Recognition | ✓ Link | 10 | MiSLAS | 2021-04-01 |
| Learning Imbalanced Data with Vision Transformers | ✓ Link | 10.1 | ViT-B + CB | 2022-12-05 |
| Predicting and Enhancing the Fairness of DNNs with the Curvature of Perceptual Manifolds | ✓ Link | 10.1 | De-C-TDE + Curvature Regularization | 2023-03-22 |
| Leveraging Angular Information Between Feature and Classifier for Long-tailed Learning: A Prediction Reformulation Approach | | 10.16 | L2A(S2) | 2022-12-03 |
| ResLT: Residual Learning for Long-tailed Recognition | ✓ Link | 10.3 | ResLT | 2021-01-26 |
| Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition | ✓ Link | 10.3 | RIDE | 2021-07-20 |
| Improving Tail-Class Representation with Centroid Contrastive Learning | | 10.3 | ICCL | 2021-10-19 |
| MetaSAug: Meta Semantic Augmentation for Long-Tailed Visual Recognition | ✓ Link | 10.32 | MetaSAug-LDAM | 2021-03-23 |
| Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective | ✓ Link | 10.34 | UniMix+Bayias | 2021-11-06 |
| Learning Imbalanced Data with Vision Transformers | ✓ Link | 10.5 | ViT-B + CE | 2022-12-05 |
| Escaping Saddle Points for Effective Generalization on Class-Imbalanced Data | ✓ Link | 10.6 | LDAM + DRW + SAM | 2022-12-28 |
| SAFA: Sample-Adaptive Feature Augmentation for Long-Tailed Image Classification | | 10.61 | SAFA+LDAM-DRW (ResNeXt-29) | 2022-11-06 |
| Long-tailed Visual Recognition via Gaussian Clouded Logit Adjustment | ✓ Link | 10.77 | GCLLoss | 2023-05-19 |
| Disentangling Label Distribution for Long-tailed Visual Recognition | ✓ Link | 11.22 | LADE | 2020-12-01 |
| A Simple Episodic Linear Probe Improves Visual Recognition in the Wild | ✓ Link | 11.3 | ELP | 2022-01-01 |
| Targeted Supervised Contrastive Learning for Long-Tailed Recognition | ✓ Link | 11.3 | TSC | 2021-11-27 |
| Learning Imbalanced Data with Vision Transformers | ✓ Link | 11.4 | ViT-B + LDAM | 2022-12-05 |
| Rethinking the Value of Labels for Improving Class-Imbalanced Learning | ✓ Link | 11.47 | LDAM-DRW + SSP | 2020-06-13 |
| Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect | ✓ Link | 11.5 | Causal Norm | 2020-09-28 |
| BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition | ✓ Link | 11.7 | BBN | 2019-12-05 |
| From Generalized zero-shot learning to long-tail with class descriptors | ✓ Link | 11.84 | smDRAGON | 2020-04-05 |
| Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss | ✓ Link | 11.84 | LDAM-DRW | 2019-06-18 |
| ELF: An Early-Exiting Framework for Long-Tailed Classification | | 12.00 | ELF&LDAM+DRW | 2020-06-22 |
| Exploring Balanced Feature Spaces for Representation Learning | | 12.00 | KCL | 2021-01-01 |
| Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective | ✓ Link | 12.20 | Prior-LT | 2021-11-06 |
| M2m: Imbalanced Classification via Major-to-minor Translation | ✓ Link | 12.5 | M2m | 2020-04-01 |
| Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect | ✓ Link | 12.63 | DecTDE | 2020-09-28 |
| Class-Balanced Loss Based on Effective Number of Samples | ✓ Link | 12.90 | Class-balanced Focal Loss | 2019-01-16 |
| Influence-Balanced Loss for Imbalanced Visual Classification | ✓ Link | 12.93 | IBLLoss | 2021-10-06 |
| Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss | ✓ Link | 13.21 | Class-balanced Resampling | 2019-06-18 |
| Class-Balanced Loss Based on Effective Number of Samples | ✓ Link | 13.46 | Class-balanced Reweighting | 2019-01-16 |
| Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss | ✓ Link | 13.61 | Empirical Risk Minimization (ERM, CE) | 2019-06-18 |
| Imagine by Reasoning: A Reasoning-Based Implicit Semantic Data Augmentation for Long-Tailed Classification | ✓ Link | 20.11 | RISDA | 2021-12-15 |