| medical-image-segmentation-on-synapse-multi | SETR | #20 | Avg DSC: 79.60 |
| semantic-segmentation-on-ade20k | SETR-MLA (160k, MS) | #113 | Validation mIoU: 50.28 |
| semantic-segmentation-on-cityscapes | SETR-PUP++ | #33 | Mean IoU (class): 81.64% |
| semantic-segmentation-on-cityscapes-val | SETR-PUP (80k, MS) | #34 | mIoU: 82.15 |
| semantic-segmentation-on-dada-seg | SETR (PUP, Transformer-Large) | #4 | mIoU: 31.8 |
| semantic-segmentation-on-dada-seg | SETR (MLA, Transformer-Large) | #5 | mIoU: 30.4 |
| semantic-segmentation-on-densepass | SETR (PUP, Transformer-L) | #18 | mIoU: 35.7% |
| semantic-segmentation-on-densepass | SETR (MLA, Transformer-L) | #19 | mIoU: 35.6% |
| semantic-segmentation-on-foodseg103 | SeTR-MLA (ViT-16/B) | #2 | mIoU: 45.1 |
| semantic-segmentation-on-foodseg103 | SeTR-Naive (ViT-16/B) | #5 | mIoU: 41.3 |
| semantic-segmentation-on-pascal-context | SETR-MLA (16, 80k, MS) | #23 | mIoU: 55.83 |
| semantic-segmentation-on-urbanlf | SETR (ViT-Large) | #9 | mIoU (Syn): 77.69mIoU (Real): 77.74 |