Far-OOD Detection on ImageNet 200
93.9AUROCASH
Evaluation results
| Method | Links | ||
|---|---|---|---|
| ASHLearning Setup=Post-hoc inference methods2025.11 | 93.9 | 27.29 | |
| KNNLearning Setup=Post-hoc inference methods2025.11 | 93.16 | 27.27 | |
| LogitNormLearning Setup=Training methods without outliers2025.11 | 93.04 | 26.11 | |
| G-ODINLearning Setup=Training methods without outliers2025.11 | 92.33 | 30.18 | |
| ReActLearning Setup=Post-hoc inference methods2025.11 | 92.31 | 28.5 | |
| RankOODLearning Setup=Training methods without outliers2025.11 | 92.14 | 27.73 | |
| ExCeLLearning Setup=Post-hoc inference methods2025.11 | 91.97 | 28.45 | |
| GENLearning Setup=Post-hoc inference methods2025.11 | 91.36 | 32.1 | |
| VIMLearning Setup=Post-hoc inference methods2025.11 | 91.26 | 27.2 | |
| MLSLearning Setup=Post-hoc inference methods2025.11 | 91.11 | 34.03 | |
| CRAFTLearning Setup=Training methods without outliers2025.11 | 90.88 | 32.67 | |
| EBOLearning Setup=Post-hoc inference methods2025.11 | 90.86 | 34.86 | |
| TempScaleLearning Setup=Post-hoc inference methods2025.11 | 90.82 | 34 | |
| CIDERLearning Setup=Training methods without outliers2025.11 | 90.66 | 30.17 | |
| ConfBranchLearning Setup=Training methods without outliers2025.11 | 90.43 | 34.75 | |
| MSPLearning Setup=Post-hoc inference methods2025.11 | 90.13 | 35.43 | |
| OELearning Setup=Training methods with outliers2025.11 | 89.02 | 34.17 | |
| MCDLearning Setup=Training methods with outliers2025.11 | 88.94 | 29.93 | |
| MixOELearning Setup=Training methods with outliers2025.11 | 88.27 | 40.93 | |
| RMDSLearning Setup=Post-hoc inference methods2025.11 | 88.06 | 32.45 | |
| UDGLearning Setup=Training methods with outliers2025.11 | 82.09 | 62.04 |