update UI

app.py

@@ -47,9 +47,27 @@ Upload your own human object interaction image and get full 3D reconstruction!
 }
 ```
 """
+citation_str = """
+## Citation
+```
+@inproceedings{xie2023template_free,
+    title = {Template Free Reconstruction of Human-object Interaction with Procedural Interaction Generation},
+    author = {Xie, Xianghui and Bhatnagar, Bharat Lal and Lenssen, Jan Eric and Pons-Moll, Gerard},
+    booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
+    month = {June},
+    year = {2024},
+}
+"""
 
 html_str = """
 <h2 style="text-align:center; color:#10768c">HDM Demo: Upload you own human object interaction image and get full 3D reconstruction!</h2>
+<h3 style="text-align:center; color:#10768c">Official Demo of "Template Free Reconstruction of Human Object Interaction with Procedural Generation", CVPR'24. </h3>
+<h3 style="text-align:center; color:#10768c"><a href="https://virtualhumans.mpi-inf.mpg.de/procigen-hdm/" target="_blank">Project Page</a> | 
+    <a href="https://github.com/xiexh20/HDM" target="_blank">Code</a> | 
+    <a href="https://edmond.mpg.de/dataset.xhtml?persistentId=doi:10.17617/3.2VUEUS" target="_blank">ProciGen Dataset</a> | 
+    <a href="https://virtualhumans.mpi-inf.mpg.de/procigen-hdm/paper-lowreso.pdf" target="_blank">Paper</a>    
+</h3>
+
 <p style="text-align:left; color:#10768c">Instruction:
 <ol>
     <li>Upload an RGB image of human object interaction.</li>
@@ -61,11 +79,9 @@ html_str = """
     <li>You can view the result at `Reconstructed point cloud` and download the point cloud at `download results`. </li>
 </ol>
 Alternatively, you can click one of the examples below and start reconstruction. 
-
-Have fun!
 </p>
-
-
+<p>More example results can be found in our <a href="https://virtualhumans.mpi-inf.mpg.de/procigen-hdm/" target="_blank">Project Page</a>.</p>
+<p>Have fun! </p>
 """
 
 def plot_points(colors, coords):
@@ -165,9 +181,7 @@ def main(cfg: ProjectConfig):
     # Setup interface
     demo = gr.Blocks(title="HDM Interaction Reconstruction Demo")
     with demo:
-        gr.Markdown(md_description)
         gr.HTML(html_str)
-
         # Input data
         with gr.Row():
             input_rgb = gr.Image(label='Input RGB', type='numpy')
@@ -177,20 +191,19 @@ def main(cfg: ProjectConfig):
             with gr.Column():
                 input_std = gr.Number(label='Gaussian std coverage', value=3.5,
                                       info="This value is used to estimate camera translation to project the points."
-                                           "The larger value, the camera is farther away. It is category-dependent."
+                                           "The larger value, the camera is farther away. It is category-dependent. "
                                            "We empirically found these values are suitable: backpack-3.5, ball-3.0, bottle-3.0,"
                                            "box-3.5, chair-3.8, skateboard-3.0, suitcase-3.2, table-3.5. "
                                            "If you are not sure, 3.5 is a good start point.")
                 input_cls = gr.Dropdown(label='Object category',
-                                        info='We have fine tuned the model for some specific categories. '
+                                        info='We fine tuned the model for some specific categories. '
                                              'Reconstructing using these models should lead to better result '
                                              'for these specific categories. Simply select the category that '
                                              'fits the object from input image.',
                                         choices=['general', 'backpack', 'ball', 'bottle', 'box',
                                                  'chair', 'skateboard', 'suitcase', 'table'],
                                         value='general')
-                input_seed = gr.Number(label='Random seed', value=42,
-                                       info='Seed for the reverse diffusion process.')
+                input_seed = gr.Number(label='Random seed', value=42)
         # Output visualization
         with gr.Row():
             pc_plot = gr.Plot(label="Reconstructed point cloud")
@@ -219,6 +232,8 @@ def main(cfg: ProjectConfig):
 
         ], inputs=[input_rgb, input_mask_hum, input_mask_obj, input_std, input_seed, input_cls],)
 
+        gr.Markdown(citation_str)
+
     # demo.launch(share=True)
     # Enabling queue for runtime>60s, see: https://github.com/tloen/alpaca-lora/issues/60#issuecomment-1510006062
     demo.queue().launch(share=cfg.run.share)