update

app.py

@@ -52,12 +52,18 @@ infer_api = InferAPI(config_canocalize, config_multiview, config_slrm, config_re
 _HEADER_ = '''
 <h2><b>[CVPR 2025] StdGEN 🤗 Gradio Demo</b></h2>
 This is official demo for our CVPR 2025 paper <a href="">StdGEN: Semantic-Decomposed 3D Character Generation from Single Images</a>.
+
 Code: <a href='https://github.com/hyz317/StdGEN' target='_blank'>GitHub</a>. Paper: <a href='https://arxiv.org/abs/2411.05738' target='_blank'>ArXiv</a>.
+
 ❗️❗️❗️**Important Notes:**
-1. - You can upload any reference image (with or without background). A-pose images are also supported (white bkg required).
+1. Refinement stage takes about ~3min, please be patient.
+
+2. - You can upload any reference image (with or without background). A-pose images are also supported (white bkg required).
    - If the image has an alpha channel (transparency), background segmentation will be automatically performed. Alternatively, you can pre-segment the background using other tools and upload the result directly.  
-2. Real person images generally work well, but note that normals may appear smoother than expected. You can try to use other monocular normal estimation models.
-3. The base human model in the output is uncolored due to potential NSFW concerns. If you need colored results, please refer to the official GitHub repository for instructions.
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+3. Real person images generally work well, but note that normals may appear smoother than expected. You can try to use other monocular normal estimation models.
+
+4. The base human model in the output is uncolored due to potential NSFW concerns. If you need colored results, please refer to the official GitHub repository for instructions.
 '''
 
 _CITE_ = r"""