model noth method

README.md

@@ -202,10 +202,10 @@ all    60.456  73.261
 
 ##### Weighted Mean IoU (official metric)
 
-| method | #paramters | average | Barsana (scene 1) | Comana (scene 2) | Norway (scene 3) |
+| Model | #paramters | average | Barsana (scene 1) | Comana (scene 2) | Norway (scene 3) |
 |:-|:-|:-|:-|:-|:-|
-| [PHG-MAE](https://arxiv.org/pdf/2510.10068){^2} | 4.4M | 55.32 | 63.80 | 63.18 | 38.98 |
 | [PHG-MAE-Distil](https://arxiv.org/pdf/2510.10068){^2} | 4.4M | 56.27 | 66.34 | 61.11 | 37.69 |
+| [PHG-MAE](https://arxiv.org/pdf/2510.10068){^2} | 4.4M | 55.32 | 63.80 | 63.18 | 38.98 |
 | [Mask2Former](https://openaccess.thecvf.com/content/CVPR2022/papers/Cheng_Masked-Attention_Mask_Transformer_for_Universal_Image_Segmentation_CVPR_2022_paper.pdf) | 216M | 53.97 | 63.37 | 60.55 | 37.98 |
 | [NGC(LR)](https://openaccess.thecvf.com/content/ICCV2023W/LIMIT/papers/Marcu_Self-Supervised_Hypergraphs_for_Learning_Multiple_World_Interpretations_ICCVW_2023_paper.pdf) | 32M | 40.76  | 46.51 | 45.59 | 30.17 |
 | [NGC-Distil](https://openaccess.thecvf.com/content/ICCV2023W/LIMIT/papers/Marcu_Self-Supervised_Hypergraphs_for_Learning_Multiple_World_Interpretations_ICCVW_2023_paper.pdf) | 32M | 40.31  | n/a | n/a | n/a |
@@ -215,7 +215,7 @@ all    60.456  73.261
 
 ##### F1 Score
 
-| method | #paramters | average | Barsana (scene 1) | Comana (scene 2) | Norway (scene 3) |
+| Model | #paramters | average | Barsana (scene 1) | Comana (scene 2) | Norway (scene 3) |
 |:-|:-|:-|:-|:-|:-|
 | [PHG-MAE](https://arxiv.org/pdf/2510.10068){^2} | 4.4M | 66.09 | 75.98 | 76.12 | 46.18 |
 | [PHG-MAE-Distil](https://arxiv.org/pdf/2510.10068){^2} | 4.4M | 65.60 | 77.21 | 74.47 | 45.13 |