Semantic Segmentation on DLRSD
91.58mIoURSKT-Seg
Evaluation results
| Method | Links | ||
|---|---|---|---|
| RSKT-SegBackbone=ViT-L, Training Dataset=DLRSD2026.04 | 91.58 | 95.41 | |
| DR-SegBackbone=ViT-L, Training Dataset=DLRSD2026.04 | 91.13 | 95.15 | |
| DR-SegBackbone=ViT-B, Training Dataset=DLRSD2026.04 | 90.91 | 95.27 | |
| RSKT-SegBackbone=ViT-B, Training Dataset=DLRSD2026.04 | 90.6 | 94.89 | |
| OVRSBackbone=ViT-L, Training Dataset=DLRSD2026.04 | 88.85 | 93.64 | |
| Cat-SegBackbone=ViT-L, Training Dataset=DLRSD2026.04 | 88.68 | 93.34 | |
| SEDBackbone=ConvNeXt-L, Training Dataset=DLRSD2026.04 | 87.68 | 91.24 | |
| SANBackbone=ViT-L, Training Dataset=DLRSD2026.04 | 86.45 | 91.25 | |
| GSNetBackbone=ViT-L, Training Dataset=DLRSD2026.04 | 86.02 | 91.48 | |
| OVRSBackbone=ViT-B, Training Dataset=DLRSD2026.04 | 85.98 | 91.52 | |
| Cat-SegBackbone=ViT-B, Training Dataset=DLRSD2026.04 | 85.84 | 91.44 | |
| SANBackbone=ViT-B, Training Dataset=DLRSD2026.04 | 85.73 | 91.03 | |
| SEDBackbone=ConvNeXt-B, Training Dataset=DLRSD2026.04 | 85.13 | 91.36 | |
| GSNetBackbone=ViT-B, Training Dataset=DLRSD2026.04 | 84.12 | 90.53 | |
| SCANBackbone=ViT-L, Training Dataset=DLRSD2026.04 | 52.42 | 72.43 | |
| SCANBackbone=ViT-B, Training Dataset=DLRSD2026.04 | 48.52 | 68.68 | |
| Pi-SegBackbone=ViT-L, Type=OVRSIS, Training Dataset=iSAID2026.04 | 33.67 | 59.44 | |
| OVRSBackbone=ViT-L, Training Dataset=iSAID2026.04 | 32.25 | 60.35 | |
| OVRSBackbone=ViT-L, Type=OVRSIS, Training Dataset=iSAID2026.04 | 32.25 | 60.35 | |
| DR-SegBackbone=ViT-L, Training Dataset=iSAID2026.04 | 31.98 | 64.06 | |
| RSKT-SegBackbone=ViT-L, Training Dataset=iSAID2026.04 | 31.57 | 61.66 | |
| RSKT-SegBackbone=ViT-L, Type=OVRSIS, Training Dataset=iSAID2026.04 | 31.57 | 61.66 | |
| GSNetBackbone=ViT-L, Training Dataset=iSAID2026.04 | 31.5 | 63.05 | |
| GSNetBackbone=ViT-L, Type=OVRSIS, Training Dataset=iSAID2026.04 | 31.5 | 63.05 | |
| DR-SegBackbone=ViT-B, Training Dataset=iSAID2026.04 | 28.84 | 59.22 | |
| Cat-SegBackbone=ViT-L, Training Dataset=iSAID2026.04 | 28.8 | 59.56 | |
| Cat-SegBackbone=ViT-L, Type=OVS, Training Dataset=iSAID2026.04 | 28.8 | 59.56 | |
| GSNetBackbone=ViT-B, Training Dataset=iSAID2026.04 | 26.2 | 57.07 | |
| GSNetBackbone=ViT-B, Type=OVRSIS, Training Dataset=iSAID2026.04 | 26.2 | 57.07 | |
| RSKT-SegBackbone=ViT-B, Training Dataset=iSAID2026.04 | 24.8 | 55.94 | |
| RSKT-SegBackbone=ViT-B, Type=OVRSIS, Training Dataset=iSAID2026.04 | 24.8 | 55.94 | |
| SEDBackbone=ConvNeXt-L, Training Dataset=iSAID2026.04 | 23.8 | 50.36 | |
| SEDBackbone=ConvNeXt-L, Type=OVS, Training Dataset=iSAID2026.04 | 23.8 | 50.36 | |
| Pi-SegBackbone=ViT-B, Type=OVRSIS, Training Dataset=iSAID2026.04 | 23.62 | 50.82 | |
| SEDBackbone=ConvNeXt-B, Training Dataset=iSAID2026.04 | 21.48 | 45.15 | |
| SEDBackbone=ConvNeXt-B, Type=OVS, Training Dataset=iSAID2026.04 | 21.48 | 45.15 | |
| SCANBackbone=ViT-L, Training Dataset=iSAID2026.04 | 21.44 | 53.26 | |
| SCANBackbone=ViT-L, Type=OVS, Training Dataset=iSAID2026.04 | 21.44 | 53.26 | |
| OVRSBackbone=ViT-B, Training Dataset=iSAID2026.04 | 21.06 | 45.48 | |
| OVRSBackbone=ViT-B, Type=OVRSIS, Training Dataset=iSAID2026.04 | 21.06 | 45.48 | |
| SANBackbone=ViT-L, Training Dataset=iSAID2026.04 | 20.54 | 49.32 | |
| SANBackbone=ViT-L, Type=OVS, Training Dataset=iSAID2026.04 | 20.54 | 49.32 | |
| Cat-SegBackbone=ViT-B, Training Dataset=iSAID2026.04 | 20.41 | 44.08 | |
| Cat-SegBackbone=ViT-B, Type=OVS, Training Dataset=iSAID2026.04 | 20.41 | 44.08 | |
| SANBackbone=ViT-B, Training Dataset=iSAID2026.04 | 18.82 | 42.36 | |
| SANBackbone=ViT-B, Type=OVS, Training Dataset=iSAID2026.04 | 18.82 | 42.36 | |
| SCANBackbone=ViT-B, Training Dataset=iSAID2026.04 | 16.09 | 38.25 | |
| SCANBackbone=ViT-B, Type=OVS, Training Dataset=iSAID2026.04 | 16.09 | 38.25 |