Semantic Segmentation on Dark Zurich
61.2mIoUCoDA
Evaluation results
| Method | Links | ||
|---|---|---|---|
| CoDABackbone=SegFormer, Scene Specificity=Scene-Agnostic2024.03 | 61.2 | — | |
| MICBackbone=SegFormer, Scene Specificity=Scene-Agnostic2024.03 | 60.2 | — | |
| HRDABackbone=SegFormer, Scene Specificity=Scene-Agnostic2024.03 | 55.9 | — | |
| SePiCo (DistCL)Backbone=MiT-B52022.04 | 54.2 | — | |
| SePiCo (DistCL)Backbone=MiT-B52022.04 | 54.2 | — | |
| SePiCoBackbone=SegFormer, Scene Specificity=Scene-Agnostic2024.03 | 54.2 | — | |
| SePiCo (BankCL)Backbone=MiT-B52022.04 | 53.3 | — | |
| SePiCo (BankCL)Backbone=MiT-B52022.04 | 53.3 | — | |
| SePiCo (ProtoCL)Backbone=MiT-B52022.04 | 52.7 | — | |
| SePiCo (ProtoCL)Backbone=MiT-B52022.04 | 52.7 | — | |
| DAFormerBackbone=MiT-B52022.04 | 48.5 | — | |
| DAFormerBackbone=MiT-B52022.04 | 48.5 | — | |
| DAFormerBackbone=SegFormer, Scene Specificity=Scene-Agnostic2024.03 | 48.5 | — | |
| CDAdaBackbone=RefineNet2022.04 | 45 | — | |
| CDAdaBackbone=RefineNet2022.04 | 45 | — | |
| DANNetBackbone=RefineNet, Scene Specificity=Scene-Specialized2024.03 | 44.3 | — | |
| MGCDABackbone=RefineNet2022.04 | 42.5 | — | |
| MGCDABackbone=RefineNet2022.04 | 42.5 | — | |
| MCGDABackbone=RefineNet, Scene Specificity=Scene-Specialized2024.03 | 42.5 | — | |
| GCMABackbone=RefineNet2022.04 | 42 | — | |
| GCMABackbone=RefineNet2022.04 | 42 | — | |
| GCMABackbone=RefineNet, Scene Specificity=Scene-Specialized2024.03 | 42 | — | |
| SegF. MiT-B5Backbone=MiT-B52022.04 | 35 | — | |
| SegF. MiT-B5Backbone=MiT-B52022.04 | 35 | — | |
| DMAdaBackbone=RefineNet2022.04 | 32.1 | — | |
| DMAdaBackbone=RefineNet2022.04 | 32.1 | — | |
| AdaptSegBackbone=DeepLab-v2, Scene Specificity=Scene-Agnostic2024.03 | 30.4 | — | |
| AutoWeather4DSetting=w/ ours2026.03 | 24.09 | 39.73 | |
| HRDA + CosmosSetting=w/ cosmos2026.03 | 23.93 | 39.52 | |
| HRDASetting=w/o augmentation2026.03 | 23.92 | 38.29 | |
| SegFormer_PEPRTrain Mod.=RGB+E, Test Mod.=RGB2026.02 | 20.33 | 58.59 | |
| SegFormerTrain Mod.=RGB, Test Mod.=RGB2026.02 | 19.64 | 57.5 | |
| CoTICAScenario=TTA, Source dataset=GTA52025.12 | 19.6 | — | |
| SourceScenario=TTA, Source dataset=GTA52025.12 | 18.5 | — | |
| TENTScenario=TTA, Source dataset=GTA52025.12 | 18.5 | — | |
| DATScenario=TTA, Source dataset=GTA52025.12 | 17.9 | — | |
| CoTTAScenario=TTA, Source dataset=GTA52025.12 | 17.8 | — | |
| SegFormer_L2Train Mod.=RGB+E, Test Mod.=RGB2026.02 | 17.73 | 53.22 | |
| RefineNetTrain Mod.=RGB, Test Mod.=RGB2026.02 | 15.16 | — | |
| PSPNetTrain Mod.=RGB, Test Mod.=RGB2026.02 | 12.28 | — | |
| DeepLab-v2Train Mod.=RGB, Test Mod.=RGB2026.02 | 12.14 | — |