Organ-level semantic segmentation on Peach Flower
62.09mIoUSPROUT
Evaluation results
| Method | Links | |
|---|---|---|
| SPROUTPre-training Dataset=MCD-2.6M, Model Architecture=UDiT-L2026.03 | 62.09 | |
| CLIPPre-training Dataset=WIT-4M, Model Architecture=ViT-B-162026.03 | 59.61 | |
| DINOv3Pre-training Dataset=LVD-1689M, Model Architecture=ViT-B-162026.03 | 59.38 | |
| DINOv3Pre-training Dataset=LVD-1689M, Model Architecture=ViT-S-162026.03 | 58.18 | |
| DINOv2Pre-training Dataset=LVD-142M, Model Architecture=ViT-S-162026.03 | 57.86 | |
| SigLIPPre-training Dataset=WebLI-10B, Model Architecture=ViT-B-162026.03 | 57.73 | |
| DINOv3Pre-training Dataset=LVD-1689M, Model Architecture=ViT-L-162026.03 | 57.72 | |
| CLIPPre-training Dataset=WIT-4M, Model Architecture=ViT-L-142026.03 | 57.22 | |
| DINOv2Pre-training Dataset=LVD-142M, Model Architecture=ViT-B-162026.03 | 56.96 | |
| SigLIPPre-training Dataset=WebLI-10B, Model Architecture=ViT-L-162026.03 | 56.79 | |
| MSNPre-training Dataset=ImageNet-1K, Model Architecture=ViT-L-162026.03 | 56.5 | |
| DINOv2Pre-training Dataset=LVD-142M, Model Architecture=ViT-L-162026.03 | 55.16 | |
| MSNPre-training Dataset=ImageNet-1K, Model Architecture=ViT-S-162026.03 | 53.31 | |
| SPROUTPre-training Dataset=MCD-2.6M, Model Architecture=UDiT-B2026.03 | 51.71 | |
| MSNPre-training Dataset=ImageNet-1K, Model Architecture=ViT-B-162026.03 | 47.14 | |
| SPROUTPre-training Dataset=MCD-2.6M, Model Architecture=UDiT-S2026.03 | 34.34 | |
| MAEPre-training Dataset=ImageNet-1K, Model Architecture=ViT-B-162026.03 | 2.71 | |
| MAEPre-training Dataset=ImageNet-1K, Model Architecture=ViT-L-162026.03 | 2.1 |