| LIFT (ViT-L/14) |
- Top-1 Accuracy
- 53.7
|
Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts 2023-09-18 |
코드 1 |
| LIFT (ViT-B/16) |
- Top-1 Accuracy
- 52.2
|
Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts 2023-09-18 |
코드 1 |
| MAM (ViT-B/16) |
- Top-1 Accuracy
- 51.4
|
Improving Image Recognition by Retrieving from Web-Scale Image-Text Data 2023-04-11 |
연결 없음 |
| VL-LTR (ViT-B-16) |
- Top-1 Accuracy
- 50.1
|
VL-LTR: Learning Class-wise Visual-Linguistic Representation for Long-Tailed Visual Recognition 2021-11-26 |
코드 1 |
| BALLAD(ViT-B-16) |
- Top-1 Accuracy
- 49.5
|
A Simple Long-Tailed Recognition Baseline via Vision-Language Model 2021-11-29 |
코드 1 |
| BALLAD(ResNet-50×16) |
- Top-1 Accuracy
- 49.3
|
A Simple Long-Tailed Recognition Baseline via Vision-Language Model 2021-11-29 |
코드 1 |
| VL-LTR (ResNet-50) |
- Top-1 Accuracy
- 48.0
|
VL-LTR: Learning Class-wise Visual-Linguistic Representation for Long-Tailed Visual Recognition 2021-11-26 |
코드 1 |
| BALLAD(ResNet-101) |
- Top-1 Accuracy
- 47.9
|
A Simple Long-Tailed Recognition Baseline via Vision-Language Model 2021-11-29 |
코드 1 |
| RAC (ViT-B-16) |
- Top-1 Accuracy
- 47.17
|
Retrieval Augmented Classification for Long-Tail Visual Recognition 2022-02-22 |
연결 없음 |
| BALLAD(ResNet-50) |
- Top-1 Accuracy
- 46.5
|
A Simple Long-Tailed Recognition Baseline via Vision-Language Model 2021-11-29 |
코드 1 |
| APA (SE-ResNet-50) |
- Top-1 Accuracy
- 42.0
|
Adaptive Parametric Activation 2024-07-11 |
코드 1 |
| Difficulty-Net (ResNet-152) |
- Top-1 Accuracy
- 41.7
|
Difficulty-Net: Learning to Predict Difficulty for Long-Tailed Recognition 2022-09-07 |
코드 1 |
| GPaCo (ResNet-152) |
- Top-1 Accuracy
- 41.7
|
Generalized Parametric Contrastive Learning 2022-09-26 |
코드 1 · 코드 2 · 코드 3 · 코드 4 |
| NCL(ResNet-152) |
- Top-1 Accuracy
- 41.5
|
Nested Collaborative Learning for Long-Tailed Visual Recognition 2022-03-29 |
코드 1 |
| TADE |
- Top-1 Accuracy
- 41.3
- Top 1 Accuracy
- 40.9
|
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition 2021-07-20 |
코드 1 · 코드 2 |
| PaCo |
- Top-1 Accuracy
- 41.2
|
Parametric Contrastive Learning 2021-07-26 |
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 |
| OPeN (ResNet-152) |
- Top-1 Accuracy
- 40.5
|
Pure Noise to the Rescue of Insufficient Data: Improving Imbalanced Classification by Training on Random Noise Images 2021-12-16 |
코드 1 |
| IEM |
- Top-1 Accuracy
- 39.7
|
Inflated Episodic Memory With Region Self-Attention for Long-Tailed Visual Recognition 2020-06-01 |
연결 없음 |
| LDAM-DRS-RSG |
- Top-1 Accuracy
- 39.3
|
RSG: A Simple but Effective Module for Learning Imbalanced Datasets 2021-06-18 |
코드 1 |
| DisAlign |
- Top-1 Accuracy
- 39.3
|
Distribution Alignment: A Unified Framework for Long-tail Visual Recognition 2021-03-30 |
코드 1 |
| CBExperts |
- Top-1 Accuracy
- 38.9
|
Long-Tailed Recognition Using Class-Balanced Experts 2020-04-07 |
코드 1 |
| LADE |
- Top-1 Accuracy
- 38.8
|
Disentangling Label Distribution for Long-tailed Visual Recognition 2020-12-01 |
코드 1 · 코드 2 |
| BALMS |
- Top-1 Accuracy
- 38.7
|
Balanced Meta-Softmax for Long-Tailed Visual Recognition 2020-07-21 |
코드 1 |
| smDRAGON |
- Top-1 Accuracy
- 38.1
|
From Generalized zero-shot learning to long-tail with class descriptors 2020-04-05 |
코드 1 |
| CB LWS |
- Top-1 Accuracy
- 37.6
|
Decoupling Representation and Classifier for Long-Tailed Recognition 2019-10-21 |
코드 1 · 코드 2 · 코드 3 · 코드 4 |
| Online Feature Augmentation |
- Top-1 Accuracy
- 36.4
|
Feature Space Augmentation for Long-Tailed Data 2020-08-09 |
연결 없음 |
| LFME + OLTR |
- Top-1 Accuracy
- 36.2
|
Learning From Multiple Experts: Self-paced Knowledge Distillation for Long-tailed Classification 2020-01-06 |
코드 1 |
| OLTR |
- Top-1 Accuracy
- 34.1
|
Large-Scale Long-Tailed Recognition in an Open World 2019-04-10 |
코드 1 · 코드 2 |
| Domain Adaptation |
- Top-1 Accuracy
- 30.8
|
Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition from a Domain Adaptation Perspective 2020-03-24 |
코드 1 |