Update README.md

README.md

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 ---
 license: other
+
+tags:
+- Shape modeling
+- Volumetric models
+
+datasets:
+- shapenet
 ---
+
+### Model Description
+
+- SDF-StyleGAN: Implicit SDF-Based StyleGAN for 3D Shape Generation
+- Zheng, Xin-Yang and Liu, Yang and Wang, Peng-Shuai and Tong, Xin, 2022
+
+The proposed deeplearning model for 3D shape generation called signed distance field (SDF) - SDF-StyleGAN, whicH is based on StyleGAN2. The goal of this approach is to minimize the visual and geometric differences between the generated shapes and a collection of existing shapes.
+
+
+### Documents
+
+- [GitHub Repo](https://github.com/Zhengxinyang/SDF-StyleGAN)
+- [Paper - SDF-StyleGAN: Implicit SDF-Based StyleGAN for 3D Shape Generation](https://arxiv.org/pdf/2206.12055.pdf)
+  
+### Datasets
+
+ShapeNet is a comprehensive 3D shape dataset created for research in computer graphics, computer vision, robotics and related diciplines.
+
+
+- [Offical Dataset of ShapeNet](https://shapenet.org/)
+- [author's data preparation script](https://github.com/Zhengxinyang/SDF-StyleGAN)
+- [author's training data](https://pan.baidu.com/s/1nVS7wlcOz62nYBgjp_M8Yg?pwd=oj1b)
+
+
+### How to use
+
+Training snippets are published under the official GitHub repository above.
+
+### BibTeX Entry and Citation Info
+
+ ```
+@inproceedings{zheng2022sdfstylegan,
+  title = {SDF-StyleGAN: Implicit SDF-Based StyleGAN for 3D Shape Generation},
+  author = {Zheng, Xin-Yang and Liu, Yang and Wang, Peng-Shuai and Tong, Xin},
+  booktitle = {Comput. Graph. Forum (SGP)},
+  year = {2022},
+}
+ ```