Organ-level semantic segmentation on Apple Fruit
74.28IoUSPROUT
Evaluation results
| Method | Links | |
|---|---|---|
| SPROUTPre-training Dataset=MCD-2.6M, Model Architecture=UDiT-L2026.03 | 74.28 | |
| SPROUTPre-training Dataset=MCD-2.6M, Model Architecture=UDiT-B2026.03 | 73.1 | |
| SPROUTPre-training Dataset=MCD-2.6M, Model Architecture=UDiT-S2026.03 | 71.92 | |
| CLIPPre-training Dataset=WIT-4M, Model Architecture=ViT-L-142026.03 | 70.2 | |
| DINOv2Pre-training Dataset=LVD-142M, Model Architecture=ViT-L-162026.03 | 69.43 | |
| DINOv3Pre-training Dataset=LVD-1689M, Model Architecture=ViT-L-162026.03 | 69.22 | |
| DINOv2Pre-training Dataset=LVD-142M, Model Architecture=ViT-B-162026.03 | 69.18 | |
| DINOv2Pre-training Dataset=LVD-142M, Model Architecture=ViT-S-162026.03 | 67.9 | |
| CLIPPre-training Dataset=WIT-4M, Model Architecture=ViT-B-162026.03 | 67.08 | |
| SigLIPPre-training Dataset=WebLI-10B, Model Architecture=ViT-L-162026.03 | 66.99 | |
| SigLIPPre-training Dataset=WebLI-10B, Model Architecture=ViT-B-162026.03 | 66.57 | |
| MSNPre-training Dataset=ImageNet-1K, Model Architecture=ViT-B-162026.03 | 65.75 | |
| MSNPre-training Dataset=ImageNet-1K, Model Architecture=ViT-S-162026.03 | 65.73 | |
| DINOv3Pre-training Dataset=LVD-1689M, Model Architecture=ViT-S-162026.03 | 64.97 | |
| DINOv3Pre-training Dataset=LVD-1689M, Model Architecture=ViT-B-162026.03 | 64.47 | |
| MSNPre-training Dataset=ImageNet-1K, Model Architecture=ViT-L-162026.03 | 60.87 | |
| MAEPre-training Dataset=ImageNet-1K, Model Architecture=ViT-L-162026.03 | 7.97 | |
| MAEPre-training Dataset=ImageNet-1K, Model Architecture=ViT-B-162026.03 | 7.54 |