Semantic Segmentation On Llrgbd Synthetic
Metrics
mIoU
Results
Performance results of various models on this benchmark
Model Name | mIoU | Paper Title | Repository |
|---|---|---|---|
| TokenFusion (SegFormer-B2) | 64.75 | Multimodal Token Fusion for Vision Transformers | |
| SMMCL (SegFormer-B2) | 67.77 | Understanding Dark Scenes by Contrasting Multi-Modal Observations | |
| SA-Gate (ResNet-101) | 61.79 | Bi-directional Cross-Modality Feature Propagation with Separation-and-Aggregation Gate for RGB-D Semantic Segmentation | |
| SMMCL (SegNeXt-B) | 68.76 | Understanding Dark Scenes by Contrasting Multi-Modal Observations | |
| CMX (SegFormer-B2) | 66.52 | CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers | |
| ShapeConv (ResNeXt-101) | 63.26 | ShapeConv: Shape-aware Convolutional Layer for Indoor RGB-D Semantic Segmentation | |
| SMMCL (ResNet-101) | 64.40 | Understanding Dark Scenes by Contrasting Multi-Modal Observations | |
| CEN (ResNet-101) | 62.15 | Channel Exchanging Networks for Multimodal and Multitask Dense Image Prediction |
0 of 8 row(s) selected.