arxiv:2310.12190 region:us
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# DynamiCrafter (256x256) (text-)Image-to-Video/Image Animation Model Card
![row01](DynamiCrafter-256.webp)
<!-- Provide a quick summary of what the model is/does. -->

DynamiCrafter (256x256) (Text-)Image-to-Video is a video diffusion model that <br> takes in a still image as a conditioning image and text prompt describing dynamics,<br> and generates videos from it.

## Model Details

### Model Description

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DynamiCrafter, a (Text-)Image-to-Video/Image Animation approach, aims to generate <br>
short video clips (~2 seconds) from a conditioning image and text prompt.

This model was trained to generate 16 video frames at a resolution of 256x256 <br>
given a context frame of the same resolution.


- **Developed by:** CUHK & Tencent AI Lab
- **Funded by:** CUHK & Tencent AI Lab
- **Model type:** Generative (text-)image-to-video model
- **Finetuned from model:** VideoCrafter1 (256x256)

### Model Sources

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For research purpose, we recommend our Github repository (https://github.com/Doubiiu/DynamiCrafter), <br>
which includes the detailed implementations.
- **Repository:** https://github.com/Doubiiu/DynamiCrafter
- **Paper:** https://arxiv.org/abs/2310.12190
## Uses

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### Direct Use

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We develop this repository for RESEARCH purposes, so it can only be used for personal/research/non-commercial purposes.



## Limitations

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- The generated videos are relatively short (2 seconds, FPS=8).
- The model cannot render legible text.
- Faces and people in general may not be generated properly.
- The autoencoding part of the model is lossy, resulting in slight flickering artifacts.



## How to Get Started with the Model

Check out https://github.com/Doubiiu/DynamiCrafter