Update README.md

README.md

@@ -1,3 +1,51 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+---
+
+## Cinemo: Consistent and Controllable Image Animation with Motion Diffusion Models
+
+This repo contains pre-trained weights for our paper exploring image animation with motion diffusion models (Cinemo). You can find more visualizations on our [project page](https://maxin-cn.github.io/cinemo_project/).
+
+In this project, we propose a novel method called Cinemo, which can perform motion-controllable image animation with strong consistency and smoothness. To improve motion smoothness, Cinemo learns the distribution of motion residuals, rather than directly generating subsequent frames. Additionally, a structural similarity index-based method is proposed to control the motion intensity. Furthermore, we propose a noise refinement technique based on discrete cosine transformation to ensure temporal consistency. These three methods help Cinemo generate highly consistent, smooth, and motion-controlled image animation results. Compared to previous methods, Cinemo offers simpler and more precise user control and better generative performance.
+
+
+## News
+- (🔥 New) Jun. 2, 2024. 💥 The inference code is released. The checkpoint can be found [here](https://huggingface.co/maxin-cn/Cinemo/tree/main).
+
+
+## Setup
+
+First, download and set up the repo:
+
+```bash
+git clone https://github.com/maxin-cn/Cinemo
+cd Cinemo
+```
+
+We provide an [`environment.yml`](environment.yml) file that can be used to create a Conda environment. If you only want 
+to run pre-trained models locally on CPU, you can remove the `cudatoolkit` and `pytorch-cuda` requirements from the file.
+
+```bash
+conda env create -f environment.yml
+conda activate cinemo
+```
+
+
+## Animation 
+
+You can sample from our **pre-trained Cinemo models** with [`animation.py`](pipelines/animation.py). Weights for our pre-trained Cinemo model can be found [here](https://huggingface.co/maxin-cn/Cinemo/tree/main).  The script has various arguments to adjust sampling steps, change the classifier-free guidance scale, etc:
+
+```bash
+bash pipelines/animation.sh
+```
+
+## Other Applications
+
+You can also utilize Cinemo for other applications, such as motion transfer and video editing:
+
+```bash
+bash pipelines/video_editing.sh
+```
+
+## Acknowledgments
+Cinemo has been greatly inspired by the following amazing works and teams: [LaVie](https://github.com/Vchitect/LaVie) and [SEINE](https://github.com/Vchitect/SEINE), we thank all the contributors for open-sourcing.