OOD detection on SVHN (test)
0.998AUROCGeneralized (Neg)
Evaluation Results
| Method | Links | |||
|---|---|---|---|---|
| Generalized (Neg)Backbone=ResNet18-SimCLR, ID Dataset=STL102026.03 | 0.998 | 0.1 | — | |
| PIDBackbone=ResNet-34, In-distribution (ID) Dataset=CIFAR-1002026.03 | 0.9956 | — | 2.08 | |
| PALMBackbone=ResNet-34, In-distribution (ID) Dataset=CIFAR-1002026.03 | 0.9923 | — | 3.03 | |
| SCALE*Image Encoder=ResNet18, ID Dataset=CIFAR-10, ELogitNorm enhancement=true2025.04 | 0.9878 | 5.79 | — | |
| Single (Neg)Backbone=ResNet18-SimCLR, ID Dataset=STL102026.03 | 0.987 | 1.2 | — | |
| fDBD*Image Encoder=ResNet18, ID Dataset=CIFAR-10, ELogitNorm enhancement=true2025.04 | 0.9867 | 6.05 | — | |
| ReAct*Image Encoder=ResNet18, ID Dataset=CIFAR-10, ELogitNorm enhancement=true2025.04 | 0.9845 | 7.13 | — | |
| GEN*Image Encoder=ResNet18, ID Dataset=CIFAR-10, ELogitNorm enhancement=true2025.04 | 0.9841 | 7.29 | — | |
| MSP*Image Encoder=ResNet18, ID Dataset=CIFAR-10, ELogitNorm enhancement=true2025.04 | 0.9831 | 7.66 | — | |
| KNN*Image Encoder=ResNet18, ID Dataset=CIFAR-10, ELogitNorm enhancement=true2025.04 | 0.9781 | 11.44 | — | |
| NPOSBackbone=ResNet-34, In-distribution (ID) Dataset=CIFAR-1002026.03 | 0.9749 | — | 10.62 | |
| COMBOODBackbone=ResNet18-SimCLR, ID Dataset=STL102026.03 | 0.967 | 17.8 | — | |
| DMPLBackbone=ResNet-34, In-distribution (ID) Dataset=CIFAR-1002026.03 | 0.9624 | — | 16.97 | |
| Generalized (Neg, InfoNCE)Backbone=ResNet18-SimCLR, ID Dataset=STL102026.03 | 0.954 | 31.1 | — | |
| CIDERBackbone=ResNet-34, In-distribution (ID) Dataset=CIFAR-1002026.03 | 0.9517 | — | 22.95 | |
| BalCAL2025.04 | 0.9498 | 34.59 | — | |
| SSD+Backbone=ResNet-34, In-distribution (ID) Dataset=CIFAR-1002026.03 | 0.9419 | — | 31.19 | |
| Vanilla2025.04 | 0.9386 | 45.92 | — | |
| TST2025.04 | 0.9373 | 42.15 | — | |
| PLP2025.04 | 0.9364 | 44.78 | — | |
| fDBDImage Encoder=ResNet18, ID Dataset=CIFAR-10, ELogitNorm enhancement=false2025.04 | 0.9293 | 22.5 | — | |
| kNN+Backbone=ResNet-34, In-distribution (ID) Dataset=CIFAR-1002026.03 | 0.9278 | — | 39.23 | |
| KNNImage Encoder=ResNet18, ID Dataset=CIFAR-10, ELogitNorm enhancement=false2025.04 | 0.9267 | 22.6 | — | |
| CSIBackbone=ResNet-34, In-distribution (ID) Dataset=CIFAR-1002026.03 | 0.9265 | — | 44.53 | |
| GENImage Encoder=ResNet18, ID Dataset=CIFAR-10, ELogitNorm enhancement=false2025.04 | 0.9197 | 28.14 | — | |
| MSPImage Encoder=ResNet18, ID Dataset=CIFAR-10, ELogitNorm enhancement=false2025.04 | 0.9146 | 25.82 | — | |
| D-KNNBackbone=ResNet18-SimCLR, ID Dataset=STL102026.03 | 0.903 | 29.9 | — | |
| ReActImage Encoder=ResNet18, ID Dataset=CIFAR-10, ELogitNorm enhancement=false2025.04 | 0.8912 | 50.23 | — | |
| EnergyBackbone=ResNet-34, In-distribution (ID) Dataset=CIFAR-1002026.03 | 0.8525 | — | 66.91 | |
| SCALEImage Encoder=ResNet18, ID Dataset=CIFAR-10, ELogitNorm enhancement=false2025.04 | 0.8491 | 70.17 | — | |
| ODINBackbone=ResNet-34, In-distribution (ID) Dataset=CIFAR-1002026.03 | 0.8488 | — | 70.16 | |
| VimBackbone=ResNet-34, In-distribution (ID) Dataset=CIFAR-1002026.03 | 0.8462 | — | 73.42 | |
| CE+AUCOCLOOD detector=ODIN2023.08 | 0.835 | — | — | |
| VTST2025.04 | 0.835 | 60.91 | — | |
| CIDERBackbone=ResNet18-SimCLR, ID Dataset=STL102026.03 | 0.832 | 41.7 | — | |
| VOSBackbone=ResNet-34, In-distribution (ID) Dataset=CIFAR-1002026.03 | 0.828 | — | 43.24 | |
| CE+AUCOCLOOD detector=MSP2023.08 | 0.8203 | — | — | |
| AdaFLOOD detector=ODIN2023.08 | 0.8128 | — | — | |
| FL+S-ECEOOD detector=ODIN2023.08 | 0.8117 | — | — | |
| FL+AUCOCLOOD detector=MSP2023.08 | 0.8051 | — | — | |
| AdaFLOOD detector=MSP2023.08 | 0.803 | — | — | |
| MSPBackbone=ResNet-34, In-distribution (ID) Dataset=CIFAR-1002026.03 | 0.798 | — | 78.89 | |
| FL+S-AvUCOOD detector=MSP2023.08 | 0.7968 | — | — | |
| FL+S-AvUCOOD detector=ODIN2023.08 | 0.7968 | — | — | |
| FL+S-ECEOOD detector=MSP2023.08 | 0.7968 | — | — | |
| CEOOD detector=ODIN2023.08 | 0.7942 | — | — | |
| FL+AUCOCLOOD detector=ODIN2023.08 | 0.7935 | — | — | |
| CE+S-AvUCOOD detector=ODIN2023.08 | 0.789 | — | — | |
| CE+S-AvUCOOD detector=MSP2023.08 | 0.7804 | — | — | |
| CE+S-ECEOOD detector=ODIN2023.08 | 0.7769 | — | — | |
| FL+MMCEOOD detector=MSP2023.08 | 0.7757 | — | — | |
| CEOOD detector=MSP2023.08 | 0.7742 | — | — | |
| FL+MMCEOOD detector=ODIN2023.08 | 0.7741 | — | — | |
| CE+MMCEOOD detector=ODIN2023.08 | 0.7739 | — | — | |
| FL (gamma=3)OOD detector=ODIN2023.08 | 0.7708 | — | — | |
| CE+S-ECEOOD detector=MSP2023.08 | 0.7702 | — | — | |
| FL (gamma=3)OOD detector=MSP2023.08 | 0.7661 | — | — | |
| CE+MMCEOOD detector=MSP2023.08 | 0.7579 | — | — | |
| MSPBackbone=ResNet18-SimCLR, ID Dataset=STL102026.03 | 0.721 | 58.7 | — | |
| Energy (T=1)Backbone=ResNet18-SimCLR, ID Dataset=STL102026.03 | 0.705 | 57.8 | — | |
| CE+AUCOCLOOD detector=EBM2023.08 | 0.6969 | — | — | |
| FL+AUCOCLOOD detector=MaxLogit2023.08 | 0.6952 | — | — | |
| CE+AUCOCLOOD detector=MaxLogit2023.08 | 0.6951 | — | — | |
| FL+AUCOCLOOD detector=EBM2023.08 | 0.6946 | — | — | |
| CE+S-ECEOOD detector=EBM2023.08 | 0.6801 | — | — | |
| CE+S-ECEOOD detector=MaxLogit2023.08 | 0.6798 | — | — | |
| CE+S-AvUCOOD detector=EBM2023.08 | 0.6796 | — | — | |
| CE+S-AvUCOOD detector=MaxLogit2023.08 | 0.6793 | — | — | |
| FL+S-ECEOOD detector=EBM2023.08 | 0.6778 | — | — | |
| CEOOD detector=MaxLogit2023.08 | 0.6771 | — | — | |
| CEOOD detector=EBM2023.08 | 0.6771 | — | — | |
| FL+S-AvUCOOD detector=MaxLogit2023.08 | 0.6738 | — | — | |
| FL+S-ECEOOD detector=MaxLogit2023.08 | 0.6738 | — | — | |
| FL+S-AvUCOOD detector=EBM2023.08 | 0.6724 | — | — | |
| FL+MMCEOOD detector=MaxLogit2023.08 | 0.6697 | — | — | |
| AdaFLOOD detector=MaxLogit2023.08 | 0.6694 | — | — | |
| AdaFLOOD detector=EBM2023.08 | 0.6673 | — | — | |
| FL (gamma=3)OOD detector=MaxLogit2023.08 | 0.6669 | — | — | |
| FL+MMCEOOD detector=EBM2023.08 | 0.666 | — | — | |
| FL (gamma=3)OOD detector=EBM2023.08 | 0.6642 | — | — | |
| CE+MMCEOOD detector=MaxLogit2023.08 | 0.6634 | — | — | |
| CE+MMCEOOD detector=EBM2023.08 | 0.6623 | — | — | |
| MahalanobisBackbone=ResNet18-SimCLR, ID Dataset=STL102026.03 | 0.616 | 76.2 | — | |
| KNN (ℓ2)Backbone=ResNet18-SimCLR, ID Dataset=STL102026.03 | 0.579 | 76 | — |