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<div align="center"> <h1>FasterCache: Training-Free Video Diffusion Model Acceleration with High Quality</h1></div> <div align="center"> <a href="https://scholar.google.com/citations?user=FkkaUgwAAAAJ&hl=en" target="_blank">Zhengyao Lv</a><sup>1</sup> | <a href="https://chenyangsi.github.io/" target="_blank">Chenyang Si</a><sup>2‡</sup> | <a href="" target="_blank">Junhao Song</a><sup>3</sup> | <a href="" target="_blank">Zhenyu Yang</a><sup>3</sup> | <a href="https://mmlab.siat.ac.cn/yuqiao" target="_blank">Yu Qiao</a><sup>3</sup> | <a href="https://liuziwei7.github.io/" target="_blank">Ziwei Liu</a><sup>2†</sup> | <a href="https://i.cs.hku.hk/~kykwong/" target="_blank">Kwan-Yee K. Wong</a><sup>1†</sup> </div> <div align="center"> <sup>1</sup>The University of Hong Kong &nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <sup>2</sup>S-Lab, Nanyang Technological University <br> <sup>3</sup>Shanghai Artificial Intelligence Laboratory </div> <div align="center">(‡: Project lead; †: Corresponding authors)</div> <p align="center"> <a href="https://arxiv.org/abs/2410.19355">Paper</a> | <a href="https://vchitect.github.io/FasterCache/">Project Page</a> </p> <p align="center"> <a href="https://hits.seeyoufarm.com"><img src="https://hits.seeyoufarm.com/api/count/incr/badge.svg?url=https%3A%2F%2Fgithub.com%2FVchitect%2FFasterCache&count_bg=%2379C83D&title_bg=%23555555&icon=&icon_color=%23E7E7E7&title=Github+visitors&edge_flat=false"/></a> <a href="https://hits.seeyoufarm.com"><img src="https://hits.seeyoufarm.com/api/count/incr/badge.svg?url=https%3A%2F%2Fvchitect.github.io%2FFasterCache%2F&count_bg=%23C83D5D&title_bg=%23555555&icon=&icon_color=%23E7E7E7&title=Pages+visitors&edge_flat=false"/></a> </p>

About

We present FasterCache, a novel training-free strategy designed to accelerate the inference of video diffusion models with high-quality generation. For more details and visual results, go checkout our Project Page.

https://github.com/user-attachments/assets/035c50c2-7b74-4755-ac1e-e5aa1cffba2a

News

Usage

Installation

Run the following instructions to create an Anaconda environment.

conda create -n fastercache python=3.10 -y
conda activate fastercache
git clone https://github.com/Vchitect/FasterCache
cd FasterCache
pip install -e .

Inference

We currently support Open-Sora 1.2, Open-Sora-Plan 1.1, Latte, CogvideoX-2B&5B, Vchitect 2.0 and Mochi. You can achieve accelerated sampling by executing the scripts we provide.

BibTeX

@inproceedings{lv2024fastercache,
  title={FasterCache: Training-Free Video Diffusion Model Acceleration with High Quality},
  author={Lv, Zhengyao and Si, Chenyang and Song, Junhao and Yang, Zhenyu and Qiao, Yu and Liu, Ziwei and Kwan-Yee K. Wong},
  booktitle={arxiv},
  year={2024}
}

Acknowledgement

This repository borrows code from VideoSys, Vchitect-2.0, Mochi, and CogVideo,.Thanks for their contributions!