add Title and link to paper

app.py

@@ -33,7 +33,7 @@ min_len = 1e10
 for d in domains:
     with open(os.path.join(feat_dir, f'src_{d}_{shots}.pkl'), 'rb') as fp:
         dst_data_dict[d] = pickle.load(fp)
-        # min_len = min(min_len, len(dst_data_dict[d][0]))
+        min_len = min(min_len, len(dst_data_dict[d][0]))
 
 def query(query_index, query_domain):
     dst_data = dst_data_dict[query_domain]
@@ -56,11 +56,13 @@ def query(query_index, query_domain):
 
 demo = gr.Blocks()
 with demo:
+    gr.Markdown('#Unsupervised Domain Generalization by Learning a Bridge Across Domains')
+    gr.Markdown('This demo showcases the cross-domain retrieval capabilities of our self-supervised cross domain training as presented @CVPR 2022. For details please refer to [the paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Harary_Unsupervised_Domain_Generalization_by_Learning_a_Bridge_Across_Domains_CVPR_2022_paper.pdf)')
     gr.Markdown('## Select Query Domain: ')
     domain_drop = gr.Dropdown(domains)
 #     domain_select_button = gr.Button("Select Domain")
-    # slider = gr.Slider(0, min_len)
-    slider = gr.Slider(0, 10000)
+    slider = gr.Slider(0, min_len)
+    # slider = gr.Slider(0, 10000)
     image_button = gr.Button("Run")
 
     with gr.Row():