| 2d-semantic-segmentation-on-wildscenes | DeepLabv3 (ResNet-50) | #4 | mIoU: 43.37mIoU (Temporal DA): 43.95mIoU (Env DA): 36.12 |
| dichotomous-image-segmentation-on-dis-te1 | DeeplabV3+ | #20 | max F-Measure: 0.601weighted F-measure: 0.506MAE: 0.102… |
| dichotomous-image-segmentation-on-dis-te2 | DeeplabV3+ | #20 | max F-Measure: 0.681weighted F-measure: 0.587MAE: 0.105… |
| dichotomous-image-segmentation-on-dis-te3 | DeeplabV3+ | #20 | max F-Measure: 0.717weighted F-measure: 0.623MAE: 0.102… |
| dichotomous-image-segmentation-on-dis-te4 | DeeplabV3+ | #19 | max F-Measure: 0.715weighted F-measure: 0.621MAE: 0.111… |
| dichotomous-image-segmentation-on-dis-vd | DeeplabV3+ | #23 | max F-Measure: 0.660weighted F-measure: 0.568MAE: 0.114… |
| semantic-segmentation-on-cityscapes | DeepLabv3 (ResNet-101, coarse) | #39 | Mean IoU (class): 81.3% |
| semantic-segmentation-on-cityscapes-val | DeepLabv3 (Dilated-ResNet-101) | #57 | mIoU: 78.5% |
| semantic-segmentation-on-pascal-voc-2012 | DeepLabv3-JFT | #3 | Mean IoU: 86.9% |
| semantic-segmentation-on-pascal-voc-2012-val | DeepLabv3-JFT | #4 | mIoU: 82.7% |
| semantic-segmentation-on-selma | DeepLabV3 | #3 | mIoU: 70.7 |