Formatting

app.py

@@ -191,17 +191,20 @@ def demo_run(image: str,
 
 
 markdown_description = """
+    # SceneDINO Demo
+
     [Paper](https://arxiv.org/abs/xxxx.xxxxx) | [Code](https://github.com/tum-vision/scenedino) | [Project Page](https://visinf.github.io/scenedino/)
-    Upload a single image to infer 3D geometry and semantics with **SceneDINO**. You can find some example images below.
 
-    - **Feature PCA**
-    We visualize our high-dimensional feature field using PCA and visualizing three of the components in RGB. Interactively adjust which are visualized.
-    - **SSC** (Semantic Scene Completion)
-    Our features are used downstream for semantic predictions. Choose between the fully unsupervised approach or the linear probing approach.
+    Upload a single image to infer 3D geometry and semantics with **SceneDINO**. You can find some example images below.
 
     <span style="color:orange">⚠️ NOTE: We assume the intrinsic camera matrix of KITTI-360, images are cropped and rescaled to 192x640. Further note our demo's voxel limit of 5M. </span>
     """
 
+    # - **Feature PCA**
+    # We visualize our high-dimensional feature field using PCA and visualizing three of the components in RGB. Interactively adjust which are visualized.
+    # - **SSC** (Semantic Scene Completion)
+    # Our features are used downstream for semantic predictions. Choose between the fully unsupervised approach or the linear probing approach.
+
 demo = gr.Interface(
     demo_run,
     inputs=[
@@ -222,7 +225,7 @@ demo = gr.Interface(
                    camera_position=[-90, 80, None], 
                    display_mode="solid"),
     ],
-    title="SceneDINO Demo",
+    title="",
     examples="demo_utils/examples",
     description=markdown_description,
 )