| semantic-segmentation-on-bjroad | CMNeXt | #1 | IoU: 63.22 |
| semantic-segmentation-on-ddd17 | CMNeXt | #2 | mIoU: 72.67 |
| semantic-segmentation-on-deliver | CMNeXt (RGB-D-E-LiDAR) | #5 | mIoU: 66.30 |
| semantic-segmentation-on-deliver-1 | CMNeXt (RGB-D-E-LiDAR) | #3 | mIoU: 66.30 |
| semantic-segmentation-on-deliver-1 | CMNeXt (RGB-D-LiDAR) | #4 | mIoU: 65.50 |
| semantic-segmentation-on-deliver-1 | CMNeXt (RGB-D-Event) | #5 | mIoU: 64.44 |
| semantic-segmentation-on-deliver-1 | CMNeXt (RGB-Depth) | #6 | mIoU: 63.58 |
| semantic-segmentation-on-deliver-1 | CMNeXt (RGB-LiDAR) | #7 | mIoU: 58.04 |
| semantic-segmentation-on-deliver-1 | CMNeXt (RGB-Event) | #8 | mIoU: 57.48 |
| semantic-segmentation-on-dsec | CMNeXt | #2 | mIoU: 72.54 |
| semantic-segmentation-on-kitti-360 | CMNeXt (RGB-D-E-LiDAR) | #1 | mIoU: 67.84 |
| semantic-segmentation-on-mcubes | CMNeXt (B2 RGB-A-D-N) | #10 | mIoU: 51.54% |
| semantic-segmentation-on-mcubes | CMNeXt (B2 RGB-A-D) | #17 | mIoU: 49.48% |
| semantic-segmentation-on-mcubes | CMNeXt (B2 RGB-A) | #18 | mIoU: 48.42% |
| semantic-segmentation-on-mcubes-p | CMNeXt (B2 RGB-A-D) | #7 | mIoU: 49.48 |
| semantic-segmentation-on-mcubes-p | CMNeXt (B2 RGB-A) | #8 | mIoU: 48.42 |
| semantic-segmentation-on-nyu-depth-v2 | CMNeXt (B4) | #14 | Mean IoU: 56.9% |
| semantic-segmentation-on-porto | CMNeXt | #1 | IoU: 73.12 |
| semantic-segmentation-on-tlcgis | CMNeXt | #3 | IoU: 82.26 |
| semantic-segmentation-on-urbanlf | CMNeXt (RGB-LF80) | #1 | mIoU (Syn): 81.02mIoU (Real): 83.11 |
| semantic-segmentation-on-urbanlf | CMNeXt (RGB-LF33) | #2 | mIoU (Syn): 80.98mIoU (Real): 82.62 |
| semantic-segmentation-on-urbanlf | CMNeXt (RGB-LF8) | #3 | mIoU (Syn): 80.74mIoU (Real): 83.22 |
| thermal-image-segmentation-on-mfn-dataset | CMNeXt (B4) | #5 | mIOU: 59.9 |
| thermal-image-segmentation-on-noisy-rs-rgb-t | CMNeXt (B4) | #1 | mIoU: 60.3 |