Image Classification on CIFAR-100 (test) (20%, 50%, 80%, 90% Noise Accuracy)
80.1Acc (20% Noise)L2B-C2D
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| L2B-C2DNoise type=Symmetric2022.02 | 80.1 | 78.1 | 69.6 | 60.7 | |
| AugDescNoise type=Symmetric2022.02 | 79.5 | 77.2 | 66.4 | 41.2 | |
| UniConNoise type=Symmetric2022.02 | 78.9 | 77.6 | 63.9 | 44.8 | |
| L2B-UniConNoise type=Symmetric2022.02 | 78.8 | 77.3 | 67.6 | 49.6 | |
| C2DNoise type=Symmetric2022.02 | 78.7 | 76.4 | 67.8 | 58.7 | |
| TCLNoise type=Symmetric2022.02 | 78 | 73.3 | 65 | 54.5 | |
| L2B-DivideMixNoise type=Symmetric2022.02 | 77.9 | 75.9 | 62.2 | 35.8 | |
| DivideMixNoise type=Symmetric2022.02 | 77.3 | 74.6 | 60.2 | 31.5 | |
| Sel-CL+Noise type=Symmetric2022.02 | 76.5 | 72.4 | 59.6 | 48.8 | |
| MOIT+Noise type=Symmetric2022.02 | 75.9 | 70.6 | 47.6 | 41.8 | |
| M-correctionNoise type=Symmetric2022.02 | 73.9 | 66.1 | 48.2 | 24.3 | |
| MSLCNoise type=Symmetric2022.02 | 72.5 | 65.4 | 24.3 | 16.7 | |
| PENCILNoise type=Symmetric2022.02 | 69.4 | 57.5 | 31.1 | 15.3 | |
| Meta-LearningNoise type=Symmetric2022.02 | 68.5 | 59.2 | 42.4 | 19.5 | |
| GCENoise type=Symmetric2022.02 | 68.1 | 53.3 | 22.1 | 8.9 | |
| MixupNoise type=Symmetric2022.02 | 67.8 | 57.3 | 30.8 | 14.6 | |
| MLCNoise type=Symmetric2022.02 | 66.8 | 52.7 | 21.8 | 15 | |
| Co-teaching+Noise type=Symmetric2022.02 | 65.6 | 51.8 | 27.9 | 13.7 |