Add library name

README.md

@@ -1,10 +1,11 @@
 ---
 license: etalab-2.0
+pipeline_tag: image-segmentation
+library_name: pytorch
 tags:
 - semantic segmentation
 - pytorch
 - landcover
-
 model-index:
 - name: FLAIR-HUB_LC-G_utae
   results:
@@ -14,61 +15,71 @@ model-index:
       name: IGNF/FLAIR-HUB/
       type: earth-observation-dataset
     metrics:
-    - name: mIoU
-      type: mIoU
+    - type: mIoU
       value: 34.239
-    - name: Overall Accuracy
-      type: OA
+      name: mIoU
+    - type: OA
       value: 57.826
-    - name: IoU building
-      type: IoU
+      name: Overall Accuracy
+    - type: IoU
       value: 34.908
-    - name: IoU greenhouse
-      type: IoU
+      name: IoU building
+    - type: IoU
       value: 0.0
-    - name: IoU swimming pool
-      type: IoU
+      name: IoU greenhouse
+    - type: IoU
       value: 61.59
-    - name: IoU impervious surface
-      type: IoU
+      name: IoU swimming pool
+    - type: IoU
       value: 38.267
-    - name: IoU pervious surface
-      type: IoU
+      name: IoU impervious surface
+    - type: IoU
       value: 27.432
-    - name: IoU bare soil
-      type: IoU
+      name: IoU pervious surface
+    - type: IoU
       value: 33.594
-    - name: IoU water
-      type: IoU
+      name: IoU bare soil
+    - type: IoU
       value: 65.32
-    - name: IoU snow
-      type: IoU
+      name: IoU water
+    - type: IoU
       value: 67.543
-    - name: IoU herbaceous vegetation
-      type: IoU
+      name: IoU snow
+    - type: IoU
       value: 34.435
-    - name: IoU agricultural land
-      type: IoU
+      name: IoU herbaceous vegetation
+    - type: IoU
       value: 42.083
-    - name: IoU plowed land
-      type: IoU
+      name: IoU agricultural land
+    - type: IoU
       value: 10.228
-    - name: IoU vineyard
-      type: IoU
+      name: IoU plowed land
+    - type: IoU
       value: 41.105
-    - name: IoU deciduous
-      type: IoU
+      name: IoU vineyard
+    - type: IoU
       value: 55.992
-    - name: IoU coniferous
-      type: IoU
+      name: IoU deciduous
+    - type: IoU
       value: 48.219
-    - name: IoU brushwood
-      type: IoU
+      name: IoU coniferous
+    - type: IoU
       value: 14.462
-
-pipeline_tag: image-segmentation
+      name: IoU brushwood
 ---
 
+# Paper title and link
+
+The model was presented in the paper [FLAIR-HUB: Large-scale Multimodal Dataset for Land Cover and Crop Mapping](https://huggingface.co/papers/2506.07080).
+
+# Paper abstract
+
+The abstract of the paper is the following:
+
+The growing availability of high-quality Earth Observation (EO) data enables accurate global land cover and crop type monitoring. However, the volume and heterogeneity of these datasets pose major processing and annotation challenges. To address this, the French National Institute of Geographical and Forest Information (IGN) is actively exploring innovative strategies to exploit diverse EO data, which require large annotated datasets. IGN introduces FLAIR-HUB, the largest multi-sensor land cover dataset with very-high-resolution (20 cm) annotations, covering 2528 km2 of France. It combines six aligned modalities: aerial imagery, Sentinel-1/2 time series, SPOT imagery, topographic data, and historical aerial images. Extensive benchmarks evaluate multimodal fusion and deep learning models (CNNs, transformers) for land cover or crop mapping and also explore multi-task learning. Results underscore the complexity of multimodal fusion and fine-grained classification, with best land cover performance (78.2% accuracy, 65.8% mIoU) achieved using nearly all modalities. FLAIR-HUB supports supervised and multimodal pretraining, with data and code available at this https URL .
+
+## Content
+
 
 
 <div style="font-family:sans-serif; color:black; background-color:#F8F5F5; padding:25px; border-radius:10px; margin:auto; border:0px; ">
@@ -274,12 +285,12 @@ pipeline_tag: image-segmentation
   </div>
 </div>
 
-
 ---
 
 ## General Informations
 - **Contact:** flair@ign.fr
 - **Code repository:** https://github.com/IGNF/FLAIR-HUB
+- **Project page:** https://ignf.github.io/FLAIR/FLAIR-HUB/flairhub
 - **Paper:** https://arxiv.org/abs/2506.07080
 - **Developed by:** IGN
 - **Compute infrastructure:** 
@@ -362,9 +373,6 @@ pipeline_tag: image-segmentation
 | deciduous             | 55.99   | 71.79       | 67.97         | 76.06      |
 | coniferous            | 48.22   | 65.06       | 77.39         | 56.12      |
 | brushwood             | 14.46   | 25.27       | 26.54         | 24.12      |
-Selection deleted
-
-
 
 ---
 
@@ -394,18 +402,4 @@ Selection deleted
 
 ```
 @article{ign2025flairhub,
-  doi = {10.48550/arXiv.2506.07080},
-  url = {https://arxiv.org/abs/2506.07080},
-  author = {Garioud, Anatol and Giordano, Sébastien and David, Nicolas and Gonthier, Nicolas},
-  title = {FLAIR-HUB: Large-scale Multimodal Dataset for Land Cover and Crop Mapping},
-  publisher = {arXiv},
-  year = {2025}
-}
-```
-
-**APA:**
-```
-Anatol Garioud, Sébastien Giordano, Nicolas David, Nicolas Gonthier. 
-FLAIR-HUB: Large-scale Multimodal Dataset for Land Cover and Crop Mapping. (2025). 
-DOI: https://doi.org/10.48550/arXiv.2506.07080
-```
+  doi = {10.48550/arXiv.25