Fine-grained Classification on Stanford Dogs 20% symmetric noise (test)
81.4Best AccuracyDivideMix + SNSCL
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| DivideMix + SNSCLSNSCL=true2023.03 | 81.4 | 81.16 | |
| DivideMixSNSCL=false2023.03 | 79.22 | 77.86 | |
| MLC + SNSCLSNSCL=true2023.03 | 78.92 | 78.56 | |
| SYM + SNSCLSNSCL=true2023.03 | 77.55 | 77.24 | |
| MW-Net + SNSCLSNSCL=true2023.03 | 77.49 | 77.08 | |
| Label Smooth + SNSCLSNSCL=true2023.03 | 76.85 | 76.12 | |
| Cross-Entropy + SNSCLSNSCL=true2023.03 | 76.33 | 75.83 | |
| Conf. Penalty + SNSCLSNSCL=true2023.03 | 76.14 | 75.73 | |
| GCE + SNSCLSNSCL=true2023.03 | 75.99 | 74.56 | |
| JoCoR + SNSCLSNSCL=true2023.03 | 75.79 | 74.99 | |
| Co-teaching + SNSCLSNSCL=true2023.03 | 74.18 | 73.09 | |
| MLCSNSCL=false2023.03 | 74.08 | 70.51 | |
| Label SmoothSNSCL=false2023.03 | 73.51 | 64.42 | |
| Conf. PenaltySNSCL=false2023.03 | 73.22 | 66.89 | |
| Cross-EntropySNSCL=false2023.03 | 73.01 | 63.82 | |
| MW-NetSNSCL=false2023.03 | 71.99 | 69.2 | |
| SYMSNSCL=false2023.03 | 69.2 | 62.13 | |
| GCESNSCL=false2023.03 | 66.96 | 66.93 | |
| JoCoRSNSCL=false2023.03 | 66.94 | 60.81 | |
| Co-teachingSNSCL=false2023.03 | 63.71 | 58.43 |