Update README.md

README.md

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-license: apache-2.0
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+<div align="center">
+  
+# Assembler: Scalable 3D Part Assembly via Anchor Point Diffusion
+
+<a href="https://assembler3d.github.io/"><img src="https://img.shields.io/static/v1?label=Project%20Page&message=Github&color=blue&logo=github-pages"></a>&ensp;<a href="https://arxiv.org/abs/2506.17074"><img src="https://img.shields.io/badge/ArXiv-2506.17074-brightgreen"></a>&ensp;<br>
+
+**[Wang Zhao<sup>1</sup>](https://thuzhaowang.github.io), [Yan-Pei Cao<sup>2</sup>](https://yanpei.me/), [Jiale Xu<sup>1</sup>](https://bluestyle97.github.io/),  [Yuejiang Dong<sup>1,3</sup>](https://scholar.google.com.hk/citations?user=0i7bPj8AAAAJ&hl=zh-CN), [Ying Shan<sup>1</sup>](https://scholar.google.com/citations?user=4oXBp9UAAAAJ&hl=en)**
+
+<sup>1</sup>ARC Lab, Tencent PCG &ensp;&ensp;<sup>2</sup>VAST &ensp;&ensp;<sup>3</sup>Tsinghua University
+
+
+**SIGGRAPH ASIA 2025**
+
+</div>
+
+---
+
+## 🚩 Overview
+This repository contains code release for our SIGGRAPH ASIA 2025 paper "Assembler: Scalable 3D Part Assembly via Anchor Point Diffusion".
+
+
+## ⚙️ Installation
+We recommend using anaconda to install the dependencies:
+```
+conda create -n assembler python=3.10.16
+conda activate assembler
+conda install pytorch==2.6.0 torchvision==0.21.0 torchaudio==2.6.0 pytorch-cuda=12.4 -c pytorch -c nvidia
+pip install -r requirements.txt
+```
+
+## 🚀 Usage
+### Inference
+To run the inference demo, simply use:
+```
+python ./scripts/demo.py --config ./configs/demo/demo.yaml --input_dir ./examples/4ef447cbb4a72f0a0e5941c9073c4baa0babd3f93ec55d62b040915f8bf3f49c --output_dir ./outputs/4ef447
+```
+This script runs for example data inside `./examples` from Toys4k dataset. You could use your own data to assemble. Put all the part meshes (in GLB format) and reference image (in PNG format) into a single folder, and set the `input_dir` argument to that folder.
+
+```