metadata

library_name: dynamicrafter
pipeline_tag: text-to-video

DynamiCrafter (576x1024) (text-)Image-to-Video/Image Animation Model Card

DynamiCrafter (576x1024) (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 576x1024
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: DynamiCrafter (320x512)

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
Demo1: https://huggingface.co/spaces/Doubiiu/DynamiCrafter
Demo2: https://replicate.com/camenduru/dynami-crafter-576x1024

Uses

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