add intro

Author: yhZhai

README.md

@@ -1 +1,28 @@
-# [Motion Consistency Model](https://yhzhai.github.io/mcm/)
+# [Motion Consistency Model: Accelerating Video Diffusion with Disentangled Motion-Appearance Distillation](https://yhzhai.github.io/mcm/)
+
+<a href='https://yhzhai.github.io/mcm/'><img src='https://img.shields.io/badge/Project-Page-Green'></a> <a href='https://arxiv.org/abs/2406.06890'><img src='https://img.shields.io/badge/Paper-arXiv-red'></a> 
+
+[Yuanhao Zhai](https://www.yhzhai.com/)<sup>1</sup>, [Kevin Lin](https://sites.google.com/site/kevinlin311tw/)<sup>2</sup>, [Zhengyuan Yang](https://zyang-ur.github.io)<sup>2</sup>, [Linjie Li](https://scholar.google.com/citations?hl=en&user=WR875gYAAAAJ)<sup>2</sup>, [Jianfeng Wang](http://jianfengwang.me)<sup>2</sup>, [Chung-Ching Lin](https://scholar.google.com/citations?hl=en&user=legkbM0AAAAJ)<sup>2</sup>, [David Doermann](https://cse.buffalo.edu/~doermann/)<sup>1</sup>, [Junsong Yuan](https://cse.buffalo.edu/~jsyuan/)<sup>1</sup>, [Lijuan Wang](https://scholar.google.com/citations?hl=en&user=cDcWXuIAAAAJ)<sup>2</sup>
+
+**<sup>1</sup>State University of New Yort at Buffalo  &nbsp; | &nbsp;  <sup>2</sup>Microsoft**
+
+**TL;DR**: Our motion consistency model not only accelerates text2video diffusion model sampling process, but also can benefit from an additional high-quality image dataset to improve the frame quality of generated videos.
+
+![Our motion consistency model not only distill the motion prior from the teacher to accelerate sampling, but also can benefit from an additional high-quality image dataset to improve the frame quality of generated videos.](static/images/illustration.png)
+
+**All training, inference, and evaluation code, as well as model checkpoints will be released in the coming two weeks. Please stay tuned!**
+
+## :fire: News
+**[06/2024]** Paper and project page release.
+
+## Citation
+```
+@article{zhai2024motion,
+  title={Motion Consistency Model: Accelerating Video Diffusion with Disentangled
+  Motion-Appearance Distillation},
+  author={Zhai, Yuanhao and Lin, Kevin and Yang, Zhengyuan and Li, Linjie and Wang, Jianfeng and Lin, Chung-Ching and Doermann, David and Yuan, Junsong and Wang, Lijuan},
+  year={2024},
+  journal={arXiv preprint arXiv:2406.06890},
+  website={https://yhzhai.github.io/mcm/},
+}
+```