| semantic-segmentation-on-skyscapes-dense | FCN8s (ResNet-50) | #2 | Mean IoU: 33.06 |
| crack-segmentation-on-crackvision12k | FCN | #3 | mIoU: 0.59842 |
| semantic-segmentation-on-event-based-segmentation | FCN | #6 | mIoU: 59.6 |
| semantic-segmentation-on-selma | FCN | #6 | mIoU: 68.2 |
| video-semantic-segmentation-on-cityscapes-val | FCN-50 [14] | #6 | mIoU: 70.1 |
| multi-tissue-nucleus-segmentation-on-kumar | FCN8 (e) | #8 | Dice: 0.797Hausdorff Distance (mm): 31.2 |
| semantic-segmentation-on-fine-grained-grass-segmentation | FCN | #9 | mIoU: 47.47 |
| semantic-segmentation-on-trans10k | FCN | #11 | mIoU: 62.75%GFLOPs: 42.23 |
| multispectral-object-detection-on-kaist | FusionRPN+BF | #14 | All Miss Rate: 51.70 |
| semantic-segmentation-on-coco-stuff-test | FCN (VGG-16) | #19 | mIoU: 22.7% |
| semantic-segmentation-on-pascal-voc-2012-test | FCN (VGG-16) | #45 | Mean IoU: 62.2% |
| semantic-segmentation-on-pascal-context | FCN-8s | #52 | mIoU: 37.8 |
| semantic-segmentation-on-nyu-depth-v2 | FCN-32s RGB-HHA | #87 | Mean Accuracy: 44 |
| semantic-segmentation-on-cityscapes-test | FCN | #88 | Mean IoU (class): 65.3% |
| semantic-segmentation-on-ade20k | FCN | #245 | Validation mIoU: 29.39 |