DynamiCrafter (256x256) (text-)Image-to-Video/Image Animation Model Card

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

Model Details

Model Description

DynamiCrafter, a (Text-)Image-to-Video/Image Animation approach, aims to generate
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
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

For research purpose, we recommend our Github repository (https://github.com/Doubiiu/DynamiCrafter),
which includes the detailed implementations.

• Repository: https://github.com/Doubiiu/DynamiCrafter
• Paper: https://arxiv.org/abs/2310.12190

Uses

Direct Use

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

Limitations

• 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