Long Tail Learning On Cifar 100 Lt R 50
Metrics
Error Rate
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | Error Rate |
|---|---|
| deit-lt-distillation-strikes-back-for-vision | 39.5 |
| balanced-contrastive-learning-for-long-tailed-1 | 43.4 |
| enhanced-long-tailed-recognition-with | - |
| metasaug-meta-semantic-augmentation-for-long | 47.73 |
| rethinking-the-value-of-labels-for-improving | 52.89 |
| parameter-efficient-long-tailed-recognition | 16.9 |
| long-tailed-visual-recognition-via-gaussian-1 | 46.4 |
| learning-prototype-classifiers-for-long | 42.25 |
| difficulty-net-learning-to-predict-difficulty | 43.1 |
| rsg-a-simple-but-effective-module-for | 51.5 |
| global-and-local-mixture-consistency-1 | 36.15 |
| parameter-efficient-long-tailed-recognition | 9.8 |
| escaping-saddle-points-for-effective | 34.72 |
| pure-noise-to-the-rescue-of-insufficient-data | 40.2 |
| improving-calibration-for-long-tailed-1 | 47.7 |
| nested-collaborative-learning-for-long-tailed | 43.2 |
| test-agnostic-long-tailed-recognition-by-test | 46.1 |
| contrastive-learning-based-hybrid-networks | 51.07 |
| feature-generation-for-long-tail | 49.1 |
| long-tailed-recognition-by-mutual-information | 41.9 |
| long-tailed-recognition-via-weight-balancing | 42.29 |
| mdcs-more-diverse-experts-with-consistency | 39.9 |
| visual-prompt-tuning | 15.2 |
| lpt-long-tailed-prompt-tuning-for-image | 10 |
| sure-survey-recipes-for-building-reliable-and | 36.87 |