update leaderboard

app.py

@@ -43,7 +43,11 @@ def build_combine_demo():
                 multiselect=False  # 单选
             )
             hi3deval_leaderboard_table = build_leaderboard_tab(hi3deval_leaderboard_file)
-            gr.Markdown(get_citation_md("hi3deval"), elem_id="ack_markdown")
+            gr.Markdown(get_citation_md("hi3deval"), elem_id="citation_markdown")
+
+        gr.Markdown("---", elem_id="intro_markdown")
+        gr.Markdown("### Acknowledgement", elem_id="ack_markdown")
+        gr.Markdown(get_ack_md, elem_id="ack_markdown")
 
         # with gr.Tab("Image-to-3D Generation", id=1):
         #     build_leaderboard_tab()

serve/markdown.py

@@ -74,7 +74,7 @@ def get_object_dimension_description_md():
 def get_leaderboard_intro_md():
     md = '''
 This leaderboard integrates results from three complementary benchmarks that span different aspects of 3D synthesis. 
-- [Hi3DEval]()
+- [Hi3DEval](https://zyh482.github.io/Hi3DEval/)
 - [3DGenBench](https://zyh482.github.io/3DGen-Bench/)
 - [GPTEval3D](https://github.com/3DTopia/GPTEval3D)
 '''
@@ -88,7 +88,7 @@ This leaderboard is evaluated using **Hi3DEval**, a straight forward scoring ben
 
 <div style="display: flex; gap: 10px; align-items: center;">
   <a href="https://zyh482.github.io/Hi3DEval/" target="_blank"><img src="{home_icon}"></a>
-  <a href="https://arxiv.org/abs/xxxx.xxxxx" target="_blank"> <img src="{arxiv_icon}"></a>
+  <a href="https://arxiv.org/abs/2508.05609" target="_blank"> <img src="{arxiv_icon}"></a>
 </div>
 
 Specifically, each dimension is assigned an absolute score within clearly defined value ranges:
@@ -105,11 +105,20 @@ Hi3DEval supports unified evaluation for both **Text-to-3D** and **Image-to-3D**
 '''
     return md
 
+
 def get_citation_md(name):
     citations = {
         "hi3deval": '''
 ```bibtex
-@article
+@misc{zhang2025hi3devaladvancing3dgeneration,
+    title={Hi3DEval: Advancing 3D Generation Evaluation with Hierarchical Validity}, 
+    author={Yuhan Zhang and Long Zhuo and Ziyang Chu and Tong Wu and Zhibing Li and Liang Pan and Dahua Lin and Ziwei Liu},
+    year={2025},
+    eprint={2508.05609},
+    archivePrefix={arXiv},
+    primaryClass={cs.CV},
+    url={https://arxiv.org/abs/2508.05609}, 
+}
         ''',
         "3dgen-bench": '''
 ```bibtex
@@ -132,4 +141,13 @@ def get_citation_md(name):
         '''
     }
     md = f"Reference:\n{citations[name.lower()]}"
+    return md
+
+def get_ack_md():
+    md  = f"""
+This project is supported by the Shanghai Artificial Intelligence Laboratory.  
+We also acknowledge the Hugging Face platform and the broader open-source community in 3D generation, whose contributions have helped shape the ecosystem that makes this work possible.  
+We are currently working on open-sourcing the automatic evaluation pipeline, and we welcome the inclusion of more 3D generation models, including both open-source and closed-source solutions.  
+We welcome feedback, model contributions, and potential collaborations. Please contact us at yhzhang4778@gmail.com.
+"""
     return md