Semantic Segmentation on Vaihingen (test)
90.3mIoUFCN + fusion + boundaries
Evaluation results
| Method | Links | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| FCN + fusion + boundaries2017.11 | 90.3 | — | — | 92.3 | 95.2 | 84.1 | 90 | 79.3 | — | — | — | — | — | |
| FuseNet2017.11 | 90.1 | — | — | 91.3 | 94.3 | 84.8 | 89.9 | 85.9 | — | — | — | — | — | |
| V-FuseNet2017.11 | 90 | — | — | 91 | 94.4 | 84.5 | 89.9 | 86.3 | — | — | — | — | — | |
| SegNet-RC2017.11 | 89.8 | — | — | 91 | 94.5 | 84.4 | 89.9 | 77.8 | — | — | — | — | — | |
| SegNetInput=IRRG2017.11 | 89.4 | — | — | 91.5 | 94.3 | 82.7 | 89.3 | 85.7 | — | — | — | — | — | |
| FCN2017.11 | 89.1 | — | — | 90.5 | 93.7 | 83.4 | 89.2 | 72.6 | — | — | — | — | — | |
| MPerSBackbone=DINOv3-LVD, Weight Scale (Parameters)=7B parameters2026.05 | 78.42 | 87.65 | — | 82.13 | 90.56 | 64.92 | 79.48 | 75.01 | 90.19 | 95.05 | 78.73 | 88.57 | 85.72 | |
| MPerSBackbone=DINOv3-LVD, Weight Scale (Parameters)=0.3B distilled weights2026.05 | 77.1 | 86.79 | — | 81.02 | 89.55 | 63.76 | 79.08 | 72.09 | 89.52 | 94.49 | 77.87 | 88.32 | 83.78 | |
| MPerSBackbone=DINOv3-SAT, Weight Scale (Parameters)=7B parameters2026.05 | 75.61 | 85.79 | — | 79.4 | 88.75 | 61.56 | 78.6 | 69.74 | 88.52 | 94.04 | 78.6 | 88.02 | 82.17 | |
| MPerSBackbone=DINOv3-SAT, Weight Scale (Parameters)=0.3B distilled weights2026.05 | 74.53 | 85.04 | — | 79.58 | 88.22 | 61.54 | 78.05 | 65.27 | 88.63 | 93.74 | 76.19 | 87.67 | 78.99 | |
| RS3MambaBackbone=VMamba-T2026.05 | 74.08 | 84.71 | — | 79.87 | 88.76 | 60.35 | 76.56 | 64.85 | 88.81 | 94.05 | 75.27 | 86.72 | 78.68 | |
| A2-FPNBackbone=ResNet-182026.05 | 73.82 | 84.45 | — | 79.59 | 88.5 | 59.3 | 75.77 | 65.34 | 88.64 | 93.9 | 74.45 | 86.22 | 79.04 | |
| SegCLIPBackbone=Swin-B2026.05 | 72.23 | 81.27 | — | 76.88 | 85.17 | 59.2 | 76.19 | 63.71 | 86.93 | 91.99 | 74.37 | 86.49 | 77.84 | |
| MAResUnetBackbone=ResNet-342026.05 | 71.12 | 81.61 | — | 79.23 | 86.47 | 58.41 | 75.3 | 56.19 | 88.22 | 92.74 | 73.74 | 85.91 | 71.95 | |
| DIS2Modality=Full Modality2026.01 | 68.88 | 80.88 | — | — | — | — | — | — | 86.25 | 90.37 | 72.59 | 83.35 | 71.83 | |
| UnetformerBackbone=ResNet-182026.05 | 68.51 | 80.63 | — | 76.19 | 84.63 | 55.63 | 74.42 | 51.68 | 86.49 | 91.67 | 71.49 | 85.33 | 68.14 | |
| SimSiamTransferModality=Full Modality2026.01 | 66.86 | 79.19 | — | — | — | — | — | — | 84.62 | 90.55 | 73.5 | 84.11 | 63.16 | |
| GEMMNetModality=Full Modality2026.01 | 66.74 | 79.07 | — | — | — | — | — | — | 85.66 | 89.96 | 72.7 | 82.79 | 64.25 | |
| MetaSegNetBackbone=Swin-B2026.05 | 66.38 | 79.07 | — | 73.41 | 82.03 | 55.96 | 73.03 | 47.49 | 84.67 | 90.13 | 71.76 | 84.41 | 64.39 | |
| mmformerModality=Full Modality2026.01 | 66.1 | 78.54 | — | — | — | — | — | — | 85.18 | 89.65 | 72.91 | 82.75 | 62.19 | |
| ShaSpecModality=Full Modality2026.01 | 65.94 | 78.62 | — | — | — | — | — | — | 84.65 | 86.32 | 73.63 | 82.83 | 65.69 | |
| DC-SwinBackbone=Swin-B2026.05 | 65.82 | 77.35 | — | 72.78 | 81.72 | 52.86 | 73.05 | 48.69 | 84.24 | 89.94 | 69.16 | 84.42 | 65.49 | |
| SimSiamModality=Full Modality2026.01 | 65.44 | 78.25 | — | — | — | — | — | — | 83.46 | 88.82 | 70.64 | 83.85 | 64.49 | |
| DIS2Modality=Missing NDSM - Only RGIR2026.01 | 65.43 | 78.46 | — | — | — | — | — | — | 83.68 | 86.29 | 71.42 | 81.61 | 69.32 | |
| FILMBackbone=self-designed2026.05 | 62.97 | 76.28 | — | 70.4 | 78.14 | 51.89 | 73.79 | 40.63 | 82.63 | 87.73 | 68.33 | 84.92 | 57.78 | |
| GEMMNetModality=Missing NDSM - Only RGIR2026.01 | 61.15 | 74.98 | — | — | — | — | — | — | 81.17 | 83.85 | 70.29 | 80.53 | 59.05 | |
| SimSiamTransferModality=Missing NDSM - Only RGIR2026.01 | 59.15 | 73.29 | — | — | — | — | — | — | 79.1 | 82.14 | 69.67 | 81.21 | 54.33 | |
| SimSiamModality=Missing NDSM - Only RGIR2026.01 | 58.48 | 72.88 | — | — | — | — | — | — | 78.29 | 81.03 | 67.25 | 81.07 | 56.75 | |
| mmformerModality=Missing NDSM - Only RGIR2026.01 | 57.88 | 72.25 | — | — | — | — | — | — | 79.43 | 80.06 | 68.8 | 79.44 | 53.52 | |
| ShaSpecModality=Missing NDSM - Only RGIR2026.01 | 57.6 | 71.94 | — | — | — | — | — | — | 78.98 | 77.29 | 68.67 | 79.77 | 54.99 | |
| DIS2Modality=Missing RGIR - Only NDSM2026.01 | 48.92 | 63.06 | — | — | — | — | — | — | 66.94 | 86.1 | 43.38 | 76.05 | 42.82 | |
| GEMMNetModality=Missing RGIR - Only NDSM2026.01 | 47.85 | 61.89 | — | — | — | — | — | — | 67.83 | 85.59 | 43.61 | 73.85 | 38.59 | |
| CorrCLIPLearning Strategy=Training-free2026.04 | 47 | — | — | — | — | — | — | — | — | — | — | — | — | |
| mmformerModality=Missing RGIR - Only NDSM2026.01 | 46.28 | 60.18 | — | — | — | — | — | — | 68.03 | 85.08 | 38.75 | 72.62 | 36.41 | |
| ShaSpecModality=Missing RGIR - Only NDSM2026.01 | 43.4 | 57.22 | — | — | — | — | — | — | 67.09 | 78.28 | 39.51 | 72.53 | 28.69 | |
| SeeCo+ProxyCLIPLearning Strategy=Training-free2026.04 | 42.5 | — | — | — | — | — | — | — | — | — | — | — | — | |
| SeeCo+SegEarth-OVLearning Strategy=Training-free2026.04 | 41.2 | — | — | — | — | — | — | — | — | — | — | — | — | |
| SimSiamTransferModality=Missing RGIR - Only NDSM2026.01 | 39.8 | 53.55 | — | — | — | — | — | — | 64.47 | 78.13 | 25.19 | 65.81 | 34.16 | |
| SeeCo+ClearCLIPLearning Strategy=Training-free2026.04 | 37.5 | — | — | — | — | — | — | — | — | — | — | — | — | |
| SimSiamModality=Missing RGIR - Only NDSM2026.01 | 37.18 | 50.98 | — | — | — | — | — | — | 64.09 | 75.47 | 22.7 | 61.83 | 30.81 | |
| ProxyCLIPLearning Strategy=Training-free2026.04 | 30.6 | — | — | — | — | — | — | — | — | — | — | — | — | |
| SegEarth-OVLearning Strategy=Training-free2026.04 | 29.1 | — | — | — | — | — | — | — | — | — | — | — | — | |
| SCLIPLearning Strategy=Training-free2026.04 | 28.4 | — | — | — | — | — | — | — | — | — | — | — | — | |
| ClearCLIPLearning Strategy=Training-free2026.04 | 27.3 | — | — | — | — | — | — | — | — | — | — | — | — | |
| MaskCLIPLearning Strategy=Training-free2026.04 | 24.7 | — | — | — | — | — | — | — | — | — | — | — | — | |
| GEMLearning Strategy=Training-free2026.04 | 24.7 | — | — | — | — | — | — | — | — | — | — | — | — | |
| CLIPLearning Strategy=Training-free2026.04 | 10.3 | — | — | — | — | — | — | — | — | — | — | — | — | |
| LSKNet-SFramework=UNetFormer2024.03 | 0.851 | 0.918 | 0.936 | — | — | — | — | — | — | — | — | — | — | |
| LSKNet-TFramework=UNetFormer2024.03 | 0.849 | 0.917 | 0.936 | — | — | — | — | — | — | — | — | — | — | |
| UNetFormer2024.03 | 0.827 | 0.904 | 0.91 | — | — | — | — | — | — | — | — | — | — | |
| BANet2024.03 | 0.814 | 0.896 | 0.905 | — | — | — | — | — | — | — | — | — | — | |
| ABCNet2024.03 | 0.813 | 0.895 | 0.907 | — | — | — | — | — | — | — | — | — | — | |
| SwiftNet2024.03 | 0.796 | 0.883 | 0.902 | — | — | — | — | — | — | — | — | — | — | |
| EaNet2024.03 | 0.787 | 0.877 | 0.897 | — | — | — | — | — | — | — | — | — | — | |
| MARESU-Net2024.03 | 0.786 | 0.877 | 0.901 | — | — | — | — | — | — | — | — | — | — | |
| ShelfNet2024.03 | 0.783 | 0.875 | 0.898 | — | — | — | — | — | — | — | — | — | — | |
| BiSeNet2024.03 | 0.758 | 0.843 | 0.871 | — | — | — | — | — | — | — | — | — | — | |
| FANet2024.03 | 0.756 | 0.854 | 0.889 | — | — | — | — | — | — | — | — | — | — | |
| BOTNet2024.03 | 0.743 | 0.848 | 0.88 | — | — | — | — | — | — | — | — | — | — | |
| Segmenter2024.03 | 0.736 | 0.841 | 0.881 | — | — | — | — | — | — | — | — | — | — | |
| DABNet2024.03 | 0.702 | 0.792 | 0.843 | — | — | — | — | — | — | — | — | — | — | |
| DANet2024.03 | 0.694 | 0.796 | 0.882 | — | — | — | — | — | — | — | — | — | — | |
| ERFNet2024.03 | 0.691 | 0.789 | 0.858 | — | — | — | — | — | — | — | — | — | — | |
| PSPNet2024.03 | 0.686 | 0.79 | 0.877 | — | — | — | — | — | — | — | — | — | — | |
| ADL_32022.06 | — | — | 88 | — | — | — | — | — | 89.5 | 93.2 | 82.3 | 88.2 | 63.3 | |
| AFNet2022.06 | — | — | 91.6 | — | — | — | — | — | 93.4 | 95.9 | 86 | 90.7 | 87.2 | |
| AREANs-ResNeSt2022.06 | — | — | 91.3 | — | — | — | — | — | 93.2 | 96.1 | 84.8 | 90.2 | 90.5 | |
| CASIA22022.06 | — | — | 91.1 | — | — | — | — | — | 93.2 | 96 | 84.7 | 89.9 | 86.7 | |
| CEGFNet2022.06 | — | — | 89.3 | — | — | — | — | — | — | — | — | — | — | |
| DeepLabV3+2024.03 | — | 0.874 | 0.89 | — | — | — | — | — | — | — | — | — | — | |
| DGCR2022.06 | — | — | 91.1 | — | — | — | — | — | 92.9 | 95.8 | 84.7 | 90.1 | 86.5 | |
| DLR_92022.06 | — | — | 90.3 | — | — | — | — | — | 92.4 | 95.2 | 83.9 | 89.9 | 81.2 | |
| DST_22022.06 | — | — | 89.1 | — | — | — | — | — | 90.5 | 93.7 | 83.4 | 89.2 | 72.6 | |
| EfficientUNetTransformerInput=IRRG2022.06 | — | — | 91.5 | — | — | — | — | — | 93.5 | 95.7 | 84.9 | 89.9 | 87.8 | |
| EfficientUNetTransformerInput=IRRG + DSM2022.06 | — | — | 91.8 | — | — | — | — | — | 94.7 | 98 | 89.4 | 90.4 | 96 | |
| EfficientUNetTransformer (No Decoder)Input=IRRG + DSM, Decoder=none2022.06 | — | — | 91.5 | — | — | — | — | — | 93.5 | 96.2 | 84.8 | 90.4 | 87.1 | |
| G2GNet2022.06 | — | — | 90.2 | — | — | — | — | — | 92.1 | 94.8 | 83.8 | 89.6 | 85.4 | |
| GSN32022.06 | — | — | 90.3 | — | — | — | — | — | 92.2 | 95.1 | 83.7 | 89.9 | 82.4 | |
| HUSTW32022.06 | — | — | 90.7 | — | — | — | — | — | 92.1 | 95.3 | 85.6 | 90.5 | 78.3 | |
| LANet2022.06 | — | — | 89.9 | — | — | — | — | — | 92.4 | 94.9 | 82.9 | 88.9 | 81.3 | |
| MF-DFNet2022.06 | — | — | 86.2 | — | — | — | — | — | 88.8 | 93.1 | 78.4 | 84 | 77.5 | |
| ONE_72022.06 | — | — | 89.8 | — | — | — | — | — | 91 | 94.5 | 84.4 | 89.9 | 77.8 | |
| RIT_72022.06 | — | — | 89.9 | — | — | — | — | — | 91.7 | 95.2 | 83.5 | 89.2 | 82.8 | |
| RIT_L2022.06 | — | — | 87.8 | — | — | — | — | — | 89.6 | 92.2 | 81.6 | 88.6 | 76 | |
| SBANet2022.06 | — | — | 90.5 | — | — | — | — | — | 94.4 | 92.9 | 83.4 | 89.6 | 91.4 | |
| SVL2022.06 | — | — | 84.8 | — | — | — | — | — | 86.6 | 91 | 77 | 85 | 55.6 | |
| Swin-B-CNN+BD2022.06 | — | — | 90.4 | — | — | — | — | — | 92.2 | 95.3 | 83.6 | 89.6 | 86.9 | |
| Swin-S2022.06 | — | — | 91.6 | — | — | — | — | — | 93.6 | 96.2 | 85.8 | 90.4 | 87.6 | |
| UFMG_42022.06 | — | — | 89.4 | — | — | — | — | — | 91.1 | 94.5 | 82.9 | 88.8 | 81.3 | |
| UZ_12022.06 | — | — | 87.3 | — | — | — | — | — | 89.2 | 92.5 | 81.6 | 86.9 | 57.3 |