Image Classification on Clothing1M
75.4AccuracyCPC
Evaluation results
| Method | Links | ||
|---|---|---|---|
| CPCBackbone=ResNet-502022.12 | 75.4 | — | |
| AugDMixBackbone=Inception-resnet v22022.12 | 75.11 | — | |
| ELR+Backbone=ResNet-502022.02 | 74.8 | — | |
| DMixBackbone=ResNet-502022.02 | 74.8 | — | |
| ELR+Backbone=Inception-resnet v22022.12 | 74.8 | — | |
| DivideMixBackbone=Inception-resnet v22022.12 | 74.76 | — | |
| DivideMixBackbone=ResNet-502022.12 | 74.76 | — | |
| BaselineBackbone=ResNet-502022.12 | 74.73 | — | |
| CleanNetBackbone=ResNet-502022.02 | 74.7 | — | |
| NCR+Mixup+DABackbone=ResNet-502022.02 | 74.6 | — | |
| NCRBackbone=ResNet-502022.12 | 74.6 | — | |
| NCR+MixupBackbone=ResNet-502022.02 | 74.5 | — | |
| NCRBackbone=ResNet-502022.02 | 74.4 | — | |
| LongReMixBackbone=Inception-resnet v22022.12 | 74.38 | — | |
| LRWOptBackbone=ViT-B/162024.03 | 73.97 | — | |
| MLNTBackbone=ResNet-50, Iterations=32022.02 | 73.5 | — | |
| IMAEBackbone=ResNet-50, Optimizer=SGD, Resolution=227x227, Batch size=842019.03 | 73.2 | — | |
| GDWBackbone=ViT-B/162024.03 | 73.12 | — | |
| LongReMixBackbone=ResNet-502022.02 | 73 | — | |
| MWNBackbone=ViT-B/162024.03 | 72.79 | — | |
| LDMIBackbone=ResNet-502022.02 | 72.5 | — | |
| MetaCleaner2025.09 | 72.5 | — | |
| MixNN2025.09 | 72.39 | — | |
| L2RBackbone=ViT-B/162024.03 | 72.22 | — | |
| MixupBackbone=ResNet-502022.02 | 72.2 | — | |
| Joint Optim.Backbone=ResNet-502019.03 | 72.2 | — | |
| Joint-Optim2025.09 | 72.16 | — | |
| FSRBackbone=ViT-B/162024.03 | 72.07 | — | |
| LRT2025.09 | 71.74 | — | |
| StandardBackbone=ResNet-502022.02 | 71.7 | — | |
| CCEBackbone=ResNet-50, Optimizer=SGD, Resolution=227x227, Batch size=84, Training=Authors re-trained2019.03 | 71.7 | — | |
| MAPLEBackbone=ViT-B/162024.03 | 71.67 | — | |
| LiLAW2025.09 | 71.44 | — | |
| Weakly Supervised2025.09 | 71.36 | — | |
| MaskingBackbone=ResNet-50, Source=Han et al. (2018)2019.03 | 71.1 | — | |
| SL2025.09 | 71.02 | — | |
| SLBackbone=ResNet-50, Source=Wang et al. (2019d)2019.03 | 71 | — | |
| SEAL2025.09 | 70.63 | — | |
| S-adaptationBackbone=ResNet-50, Source=Han et al. (2018)2019.03 | 70.3 | — | |
| Co-teaching2025.09 | 70.15 | — | |
| Forward2025.09 | 69.84 | — | |
| ForwardBackbone=ResNet-50, Source=Wang et al. (2019d)2019.03 | 69.8 | — | |
| GCEBackbone=ResNet-50, Source=Wang et al. (2019d)2019.03 | 69.8 | — | |
| GCE2025.09 | 69.75 | — | |
| D2LBackbone=ResNet-50, Source=Wang et al. (2019d)2019.03 | 69.5 | — | |
| Cross-entropy2025.09 | 69.21 | — | |
| Backward2025.09 | 69.13 | — | |
| Boot-hardBackbone=ResNet-50, Source=Wang et al. (2019d)2019.03 | 68.9 | — | |
| CCEBackbone=ResNet-50, Source=Wang et al. (2019d)2019.03 | 68.8 | — | |
| MAEBackbone=ResNet-50, Optimizer=SGD, Resolution=227x227, Batch size=84, Training=Authors re-trained2019.03 | 39.7 | — | |
| CANOLA2026.06 | — | 65.68 | |
| Co-Teaching2026.06 | — | 62.73 | |
| DivideMix2026.06 | — | 65 | |
| SCE-Loss2026.06 | — | 61.46 | |
| SiDyP2026.06 | — | 63.14 |