Semantic Segmentation on SUN RGB-D
53mIoUTokenFusion
Evaluation Results
| Method | Links | |||
|---|---|---|---|---|
| TokenFusionInputs=RGB+D, Variant=S2022.04 | 53 | 84.7 | 64.1 | |
| GT DepthArchitecture=GeminiFusion2026.04 | 52.7 | 82.8 | — | |
| SigmaBackbone=VMamba-S, Params=69.8, Input Size=480 x 6402024.04 | 52.4 | — | — | |
| CMNeXtBackbone=MiT-B4, Params=119.6, Input Size=530 x 7302024.04 | 51.9 | — | — | |
| FRNetBackbone=ResNet-34, Params=85.5, Input Size=530 x 7302024.04 | 51.8 | — | — | |
| FRNetBackbone=ResNet-34, Params=85.5M2026.05 | 51.8 | — | — | |
| TokenFusionInputs=RGB+D, Variant=Ti2022.04 | 51.4 | 84 | 63.3 | |
| GT DepthArchitecture=DFormer2026.04 | 51.2 | 83.4 | — | |
| DFormerBackbone=DFormer-Base, Params=29.5M2026.05 | 51.2 | — | — | |
| CENBackbone=ResNet-152, Params=133.9, Input Size=530 x 7302024.04 | 51.1 | — | — | |
| MultiMAEBackbone=ViT-B, Params=95.2, Input Size=640 x 6402024.04 | 51.1 | — | — | |
| CENInputs=RGB+D2022.04 | 51.1 | 83.5 | 63.2 | |
| CENBackbone=ResNet-152, Params=133.9M2026.05 | 51.1 | — | — | |
| MultiMAEBackbone=ViT-B, Params=95.2M2026.05 | 51.1 | — | — | |
| PGDENetBackbone=ResNet-34, Params=100.7, Input Size=530 x 7302024.04 | 51 | — | — | |
| TokenFusionBackbone=MiT-B3, Params=45.9, Input Size=530 x 7302024.04 | 51 | — | — | |
| PGDENetBackbone=ResNet-34, Params=100.7M2026.05 | 51 | — | — | |
| TokenFusionBackbone=MiT-B3, Params=45.9M2026.05 | 51 | — | — | |
| RelFlexformer (w/ DFormer)Backbone=DFormer-Base, Params=29.5M2026.05 | 51 | — | — | |
| TokenFusionBackbone=MiT-B2, Params=26.0, Input Size=530 x 7302024.04 | 50.3 | — | — | |
| TokenFusionBackbone=MiT-B2, Params=26.0M2026.05 | 50.3 | — | — | |
| CENBackbone=ResNet-101, Params=118.2, Input Size=530 x 7302024.04 | 50.2 | — | — | |
| CENBackbone=ResNet-101, Params=118.2M2026.05 | 50.2 | — | — | |
| SigmaBackbone=VMamba-T, Params=48.3, Input Size=480 x 6402024.04 | 50 | — | — | |
| DFormerBackbone=DFormer-Small, Params=18.7M2026.05 | 50 | — | — | |
| CMXBackbone=MiT-B2, Params=66.6M2026.05 | 49.7 | — | — | |
| PDCNetBackbone=ResNet-101, Input Size=480 x 4802024.04 | 49.6 | — | — | |
| SA-GateBackbone=ResNet-101, Params=110.9, Input Size=530 x 7302024.04 | 49.4 | — | — | |
| SA-GateBackbone=ResNet-101, Params=110.9M2026.05 | 49.4 | — | — | |
| AsymFormerBackbone=MiT-B0+ConvNeXt-Tiny, Params=33.0M2026.05 | 49.1 | — | — | |
| ConcatInputs=RGB+D, Variant=S2022.04 | 49 | 83.5 | 62 | |
| DFormerBackbone=DFormer-Tiny, Params=6.0M2026.05 | 48.8 | — | — | |
| SGNetBackbone=ResNet-101, Params=64.7, Input Size=530 x 7302024.04 | 48.6 | — | — | |
| ShapeConvBackbone=ResNext-101, Params=86.8, Input Size=530 x 7302024.04 | 48.6 | — | — | |
| SGNetBackbone=ResNet-101, Params=64.7M2026.05 | 48.6 | — | — | |
| ShapeConvBackbone=ResNet-101, Params=86.8M2026.05 | 48.6 | — | — | |
| Performer (w/ DFormer)Backbone=DFormer-Base, Params=29.5M2026.05 | 48.5 | — | — | |
| EMSANetBackbone=ResNet-34, Params=46.9, Input Size=530 x 7302024.04 | 48.4 | — | — | |
| EMSANetBackbone=ResNet-34, Params=46.9M2026.05 | 48.4 | — | — | |
| ESANetBackbone=ResNet-34, Params=31.2, Input Size=480 x 6402024.04 | 48.2 | — | — | |
| ESANetBackbone=ResNet-34, Params=31.2M2026.05 | 48.2 | — | — | |
| ACNetBackbone=ResNet-50, Params=116.6, Input Size=530 x 7302024.04 | 48.1 | — | — | |
| w/o fusionInputs=RGB, Variant=S2022.04 | 48.1 | 82.9 | 61.3 | |
| ACNetBackbone=ResNet-50, Params=116.6M2026.05 | 48.1 | — | — | |
| ConcatInputs=RGB+D, Variant=Ti2022.04 | 47.9 | 82.8 | 61.4 | |
| GeomPromptArchitecture=DFormer2026.04 | 47.8 | 81.6 | — | |
| RDFNetInputs=RGB+D2022.04 | 47.7 | 81.5 | 60.1 | |
| DA2Architecture=GeminiFusion2026.04 | 47.7 | 81.4 | — | |
| DA2 [Hypersim]Architecture=DFormer2026.04 | 47.5 | 81.8 | — | |
| RefineNetInputs=RGB2022.04 | 47 | 81.1 | 57.7 | |
| w/o fusionInputs=RGB, Variant=Ti2022.04 | 47 | 82.3 | 60.6 | |
| Metric3Dv2Architecture=DFormer2026.04 | 46.6 | 81.8 | — | |
| Metric3Dv2Architecture=GeminiFusion2026.04 | 46.6 | 80.6 | — | |
| GeomPromptArchitecture=GeminiFusion2026.04 | 46.4 | 80.3 | — | |
| RefineNet-Res152Backbone=ResNet-1522017.05 | 45.9 | 80.6 | — | |
| RefineNet-Res101Backbone=ResNet-1012017.05 | 45.7 | 80.4 | — | |
| SSMAInputs=RGB+D2022.04 | 45.7 | 81 | 58.1 | |
| OursMode=RGB-D, Backbone=FasterNet-M2026.03 | 45.56 | — | — | |
| loop2 (test-aug)Backbone=ResNet-50, Number of loops=2, Depth Usage=predicted depth, test-time augmentation=true2017.05 | 45.1 | 80.3 | — | |
| DA2 [Hypersim]Architecture=GeminiFusion2026.04 | 44.5 | 79.6 | — | |
| loop2Backbone=ResNet-50, Number of loops=2, Depth Usage=predicted depth2017.05 | 44.3 | 79.9 | — | |
| CI-NetMode=RGB, Backbone=ResNet1012026.03 | 44.3 | — | — | |
| EMSAFormerMode=RGB-D, Backbone=Swin v22026.03 | 44.13 | — | — | |
| loop1 w/ pred-depthBackbone=ResNet-50, Number of loops=1, Depth Usage=predicted depth2017.05 | 44 | 79.8 | — | |
| DA2Architecture=DFormer2026.04 | 44 | 80.8 | — | |
| loop1 w/ gt-depthBackbone=ResNet-50, Number of loops=1, Depth Usage=ground-truth depth2017.05 | 43.9 | 79.8 | — | |
| SSMAMode=RGB-D, Backbone=ResNet502026.03 | 43.9 | — | — | |
| RGB-onlyArchitecture=GeminiFusion2026.04 | 43.4 | 78.8 | — | |
| loop1 w/o depthBackbone=ResNet-50, Number of loops=1, Depth Usage=none2017.05 | 43.2 | 79.3 | — | |
| DIANetMode=RGB, Backbone=ResNet502026.03 | 43.1 | — | — | |
| X-Decoder (L)Training Data (SEG)=true, Training Data (DET)=false, Training Data (ITP)=true, Evaluation Protocol=Zero-shot, Backbone=Large2023.03 | 43 | — | — | |
| w/ pred-depthBackbone=ResNet-50, Depth Usage=predicted depth2017.05 | 42.3 | 78.9 | — | |
| Context2017.05 | 42.3 | 78.4 | — | |
| w/ gt-depthBackbone=ResNet-50, Depth Usage=ground-truth depth2017.05 | 42.2 | 78.7 | — | |
| D-CNNMode=RGB-D, Backbone=VGG-Net2026.03 | 42 | — | — | |
| OpenSeeD (L)Training Data (SEG)=true, Training Data (DET)=true, Training Data (ITP)=false, Evaluation Protocol=Zero-shot, Backbone=Large2023.03 | 41.9 | — | — | |
| RGB-onlyArchitecture=DFormer2026.04 | 41.7 | 78.3 | — | |
| baselineBackbone=ResNet-502017.05 | 40.2 | 77.6 | — | |
| 3DGNNMode=RGB-D, Backbone=VGG-Net2026.03 | 40.2 | — | — | |
| OpenSeeD (T)Training Data (SEG)=true, Training Data (DET)=true, Training Data (ITP)=false, Evaluation Protocol=Zero-shot, Backbone=Tiny2023.03 | 39 | — | — | |
| SSMAMode=RGB, Backbone=ResNet502026.03 | 38.4 | — | — | |
| FuseNetInputs=RGB+D2022.04 | 37.3 | 76.3 | 48.3 | |
| X-Decoder (T)Training Data (SEG)=true, Training Data (DET)=false, Training Data (ITP)=true, Evaluation Protocol=Zero-shot, Backbone=Tiny2023.03 | 34.5 | — | — | |
| MSeg (B)Training Data (SEG)=true, Training Data (DET)=false, Training Data (ITP)=false, Evaluation Protocol=Zero-shot, Backbone=Base2023.03 | 29.6 | — | — | |
| FCN-32sInputs=RGB2022.04 | 29 | 68.4 | 41.1 |