Enhance-A-Video

March 8, 2025 Β· View on GitHub

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This repository is the official implementation of Enhance-A-Video: Better Generated Video for Free.

πŸŽ₯ Demo

Wan2.1

HunyuanVideo

The video has been heavily compressed to GitHub's policy. For more demos, please visit our blog.

πŸ”₯πŸ”₯πŸ”₯News

πŸŽ‰ Method

method

We design an Enhance Block as a parallel branch. This branch computes the average of non-diagonal elements of temporal attention maps as cross-frame intensity (CFI). An enhanced temperature parameter multiplies the CFI to enhance the temporal attention output.

πŸ› οΈ Dependencies and Installation

Install the dependencies:

conda create -n enhanceAvideo python=3.10
conda activate enhanceAvideo
pip install -r requirements.txt

πŸ“œ Requirements

The following table shows the requirements for running HunyuanVideo/CogVideoX model (batch size = 1) to generate videos:

ModelSetting
(height/width/frame)
Denoising stepGPU Memory Usage
Wan2.1480px832px81f5050GB
HunyuanVideo720px1280px129f5060GB
CogVideoX-2B480px720px49f5020GB

🧱 Inference

Generate videos:

python cogvideox.py
python hunyuanvideo.py
python wan.py

πŸ”— BibTeX

@misc{luo2025enhanceavideobettergeneratedvideo,
      title={Enhance-A-Video: Better Generated Video for Free}, 
      author={Yang Luo and Xuanlei Zhao and Mengzhao Chen and Kaipeng Zhang and Wenqi Shao and Kai Wang and Zhangyang Wang and Yang You},
      year={2025},
      eprint={2502.07508},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2502.07508}, 
}