Home

Awesome

Legacy-Photo-Editing-with-Learned-Noise-Prior

The github page for WACV 2021 paper: Legacy Photo Editing with Learned Noise Prior

arxiv version: https://arxiv.org/abs/2011.11309

IEEE/CVF version: https://openaccess.thecvf.com/content/WACV2021/html/Zhao_Legacy_Photo_Editing_With_Learned_Noise_Prior_WACV_2021_paper.html

Legacy Photo Dataset (LP Dataset)

The proposed legacy photo dataset contains approximately 25000 legacy images crawed from the Internet. The images include the real noises. The LP Dataset can only be used for research purpose and any commercial use of the LP Dataset is not allowed.

If you would like to download the LP Dataset data, please fill out an agreement to the LP Dataset Terms of Use and send it to us at yzzhao2-c@my.cityu.edu.hk.

Please use the institutional email instead of anonymous addresses such as Gmail, QQMail, and hotmail. Make sure your email address is the same as it in the LP Dataset Terms of Use.

Some training samples are shown like:

<img src="./img/training_sample/37.jpg" width="1000"/><img src="./img/training_sample/7.jpg" width="1000"/><img src="./img/training_sample/15.jpg" width="1000"/>

Some masked samples are shown like:

<img src="./img/masked_sample/4.jpg" width="1000"/><img src="./img/masked_sample/7.jpg" width="1000"/><img src="./img/masked_sample/83.jpg" width="1000"/>

Some validation samples are shown like:

<img src="./img/val_sample/74.jpg" width="1000"/><img src="./img/val_sample/2346.jpg" width="1000"/><img src="./img/val_sample/2450.jpg" width="1000"/>

Code Usage

Requirement:

Training:

(currently no pre-trained models provided)

Reference

If you think the paper is helpful for your research, please cite:

@inproceedings{zhao2021legacy,
  title={Legacy Photo Editing with Learned Noise Prior},
  author={Zhao, Yuzhi and Po, Lai-Man and Lin, Tingyu and Wang, Xuehui and Liu, Kangcheng and Zhang, Yujia and Yu, Wing-Yin and Xian, Pengfei and Xiong, Jingjing},
  booktitle={IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
  year={2021},
  pages={2103-2112}
}