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<h1> | |
STAR: Spatial-Temporal Augmentation with Text-to-Video Models for Real-World Video Super-Resolution | |
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<a href='https://github.com/CSRuiXie' target='_blank'>Rui Xie<sup>1*</sup></a>,  | |
<a href='https://github.com/yhliu04' target='_blank'>Yinhong Liu<sup>1*</sup></a>,  | |
<a href='https://scholar.google.com/citations?user=Uhp3JKgAAAAJ&hl=zh-CN&oi=sra' target='_blank'>Chen Zhao<sup>1</sup></a>,  | |
<a href='https://scholar.google.com/citations?hl=zh-CN&user=yWq1Fd4AAAAJ' target='_blank'>Penghao Zhou<sup>2</sup></a>,  | |
<a href='https://scholar.google.com/citations?hl=zh-CN&user=Ds5wwRoAAAAJ' target='_blank'>Zhenheng Yang<sup>2</sup></a><br> | |
<a href='https://scholar.google.com/citations?hl=zh-CN&user=w03CHFwAAAAJ' target='_blank'>Jun Zhou<sup>3</sup></a>,  | |
<a href='https://cszn.github.io/' target='_blank'>Kai Zhang<sup>1</sup></a>,  | |
<a href='https://jessezhang92.github.io/' target='_blank'>Zhenyu Zhang<sup>1</sup></a>,  | |
<a href='https://scholar.google.com.hk/citations?user=6CIDtZQAAAAJ&hl=zh-CN' target='_blank'>Jian Yang<sup>1</sup></a>,  | |
<a href='https://tyshiwo.github.io/index.html' target='_blank'>Ying Tai<sup>1†</sup></a> | |
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<sup>1</sup>Nanjing University, <sup>2</sup>ByteDance,  <sup>3</sup>Southwest University | |
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<a href="https://nju-pcalab.github.io/projects/STAR" target='_blank'> | |
<img src="https://img.shields.io/badge/π-Project%20Page-blue"> | |
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<a href="https://arxiv.org/abs/2407.07667" target='_blank'> | |
<img src="https://img.shields.io/badge/arXiv-2312.06640-b31b1b.svg"> | |
</a> | |
<a href="https://youtu.be/hx0zrql-SrU" target='_blank'> | |
<img src="https://img.shields.io/badge/Demo%20Video-%23FF0000.svg?logo=YouTube&logoColor=white"> | |
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### π Updates | |
- **2024.12.01** The pretrained STAR model (I2VGen-XL version) and inference code have been released. | |
## π Method Overview | |
![STAR](assets/overview.png) | |
## π· Results Display | |
![STAR](assets/teaser.png) | |
![STAR](assets/real_world.png) | |
π More visual results can be found in our [Project Page](https://nju-pcalab.github.io/projects/STAR) and [Video Demo](https://youtu.be/hx0zrql-SrU). | |
## βοΈ Dependencies and Installation | |
``` | |
## git clone this repository | |
git clone https://github.com/NJU-PCALab/STAR.git | |
cd STAR | |
## create an environment | |
conda create -n star python=3.10 | |
conda activate star | |
pip install -r requirements.txt | |
sudo apt-get update && apt-get install ffmpeg libsm6 libxext6 -y | |
``` | |
## π Inference | |
#### Step 1: Download the pretrained model STAR from [HuggingFace](https://huggingface.co/SherryX/STAR). | |
We provide two verisions, `heavy_deg.pt` for heavy degraded videos and `light_deg.pt` for light degraded videos (e.g., the low-resolution video downloaded from video websites). | |
You can put the weight into `pretrained_weight/`. | |
#### Step 2: Prepare testing data | |
You can put the testing videos in the `input/video/`. | |
As for the prompt, there are three options: 1. No prompt. 2. Automatically generate a prompt [using Pllava](https://github.com/hpcaitech/Open-Sora/tree/main/tools/caption#pllava-captioning). 3. Manually write the prompt. You can put the txt file in the `input/text/`. | |
#### Step 3: Change the path | |
You need to change the paths in `video_super_resolution/scripts/inference_sr.sh` to your local corresponding paths, including `video_folder_path`, `txt_file_path`, `model_path`, and `save_dir`. | |
#### Step 4: Running inference command | |
``` | |
bash video_super_resolution/scripts/inference_sr.sh | |
``` | |
## β€οΈ Acknowledgments | |
This project is based on [I2VGen-XL](https://github.com/ali-vilab/VGen), [VEnhancer](https://github.com/Vchitect/VEnhancer) and [CogVideoX](https://github.com/THUDM/CogVideo). Thanks for their awesome works. | |
## πCitations | |
If our project helps your research or work, please consider citing our paper: | |
``` | |
@misc{xie2024addsr, | |
title={AddSR: Accelerating Diffusion-based Blind Super-Resolution with Adversarial Diffusion Distillation}, | |
author={Rui Xie and Ying Tai and Kai Zhang and Zhenyu Zhang and Jun Zhou and Jian Yang}, | |
year={2024}, | |
eprint={2404.01717}, | |
archivePrefix={arXiv}, | |
primaryClass={cs.CV} | |
} | |
``` | |
## π§ Contact | |
If you have any inquiries, please don't hesitate to reach out via email at `ruixie0097@gmail.com` | |