Chong Mou, Mingdeng Cao, Xintao Wang, Zhaoyang Zhang, Ying Shan, Jian Zhang
ReVideo aims to solve the problem of local video editing. The editing target includes visual content and motion trajectory modifications.
Generated by Open-Sora | Editing Result |
Input Video | Editing Result |
Input Video | Editing Result |
Input Video | Editing Result |
Input Video | Editing Result |
pip install -r requirements.txt
All models will be automatically downloaded. You can also choose to download manually from this url.
Since our ReVideo is trained based on Stable Video Diffusion, the usage guidelines for the model should follow the Stable Video Diffusion's NC-COMMUNITY LICENSE!
You can download the testset from https://huggingface.co/Adapter/ReVideo.
Inference requires at least 20GB
of GPU memory for editing a 768x1344
video.
bash configs/examples/constant_motion/head6.sh
--s_h # The abscissa of the top left corner of the editing region
--e_h # The abscissa of the lower right corner of the editing region
--s_w # The ordinate of the top left corner of the editing region
--e_w # The ordinate of the lower right corner of the editing region
--ps_h # The abscissa of the start point
--pe_h # The abscissa of the end point
--ps_w # The ordinate of the start point
--pe_w # The ordinate of the end point
--x_bias_all # Horizontal offset of reciprocating motion
--y_bias_all # Vertical offset of reciprocating motion
[2] DragNUWA: Fine-grained Control in Video Generation by Integrating Text, Image, and Trajectory
[3] DragAnything: Motion Control for Anything using Entity Representation
[4] AnyV2V: A Plug-and-Play Framework For Any Video-to-Video Editing Tasks
We appreciate the releasing code of Stable Video Diffusion.