| Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts | ✓ Link | 53.7 | | LIFT (ViT-L/14) | 2023-09-18 |
| Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts | ✓ Link | 52.2 | | LIFT (ViT-B/16) | 2023-09-18 |
| Improving Image Recognition by Retrieving from Web-Scale Image-Text Data | | 51.4 | | MAM (ViT-B/16) | 2023-04-11 |
| VL-LTR: Learning Class-wise Visual-Linguistic Representation for Long-Tailed Visual Recognition | ✓ Link | 50.1 | | VL-LTR (ViT-B-16) | 2021-11-26 |
| A Simple Long-Tailed Recognition Baseline via Vision-Language Model | ✓ Link | 49.5 | | BALLAD(ViT-B-16) | 2021-11-29 |
| A Simple Long-Tailed Recognition Baseline via Vision-Language Model | ✓ Link | 49.3 | | BALLAD(ResNet-50×16) | 2021-11-29 |
| VL-LTR: Learning Class-wise Visual-Linguistic Representation for Long-Tailed Visual Recognition | ✓ Link | 48.0 | | VL-LTR (ResNet-50) | 2021-11-26 |
| A Simple Long-Tailed Recognition Baseline via Vision-Language Model | ✓ Link | 47.9 | | BALLAD(ResNet-101) | 2021-11-29 |
| Retrieval Augmented Classification for Long-Tail Visual Recognition | | 47.17 | | RAC (ViT-B-16) | 2022-02-22 |
| A Simple Long-Tailed Recognition Baseline via Vision-Language Model | ✓ Link | 46.5 | | BALLAD(ResNet-50) | 2021-11-29 |
| Adaptive Parametric Activation | ✓ Link | 42.0 | | APA (SE-ResNet-50) | 2024-07-11 |
| Difficulty-Net: Learning to Predict Difficulty for Long-Tailed Recognition | ✓ Link | 41.7 | | Difficulty-Net (ResNet-152) | 2022-09-07 |
| Generalized Parametric Contrastive Learning | ✓ Link | 41.7 | | GPaCo (ResNet-152) | 2022-09-26 |
| Nested Collaborative Learning for Long-Tailed Visual Recognition | ✓ Link | 41.5 | | NCL(ResNet-152) | 2022-03-29 |
| Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition | ✓ Link | 41.3 | 40.9 | TADE | 2021-07-20 |
| Parametric Contrastive Learning | ✓ Link | 41.2 | | PaCo | 2021-07-26 |
| Pure Noise to the Rescue of Insufficient Data: Improving Imbalanced Classification by Training on Random Noise Images | ✓ Link | 40.5 | | OPeN (ResNet-152) | 2021-12-16 |
| Inflated Episodic Memory With Region Self-Attention for Long-Tailed Visual Recognition | | 39.7 | | IEM | 2020-06-01 |
| RSG: A Simple but Effective Module for Learning Imbalanced Datasets | ✓ Link | 39.3 | | LDAM-DRS-RSG | 2021-06-18 |
| Distribution Alignment: A Unified Framework for Long-tail Visual Recognition | ✓ Link | 39.3 | | DisAlign | 2021-03-30 |
| Long-Tailed Recognition Using Class-Balanced Experts | ✓ Link | 38.9 | | CBExperts | 2020-04-07 |
| Disentangling Label Distribution for Long-tailed Visual Recognition | ✓ Link | 38.8 | | LADE | 2020-12-01 |
| Balanced Meta-Softmax for Long-Tailed Visual Recognition | ✓ Link | 38.7 | | BALMS | 2020-07-21 |
| From Generalized zero-shot learning to long-tail with class descriptors | ✓ Link | 38.1 | | smDRAGON | 2020-04-05 |
| Decoupling Representation and Classifier for Long-Tailed Recognition | ✓ Link | 37.6 | | CB LWS | 2019-10-21 |
| Feature Space Augmentation for Long-Tailed Data | | 36.4 | | Online Feature Augmentation | 2020-08-09 |
| Learning From Multiple Experts: Self-paced Knowledge Distillation for Long-tailed Classification | ✓ Link | 36.2 | | LFME + OLTR | 2020-01-06 |
| Large-Scale Long-Tailed Recognition in an Open World | ✓ Link | 34.1 | | OLTR | 2019-04-10 |
| Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition from a Domain Adaptation Perspective | ✓ Link | 30.8 | | Domain Adaptation | 2020-03-24 |