Awesome
Practical Wide-Angle Portraits Correction with Deep Structured Models
Jing Tan, Shan Zhao, Pengfei Xiong, Jiangyu Liu, Haoqiang Fan, Shuaicheng Liu
<div align="center"> <img src="figures/cvpr21_poster_latest.png"/> </div><br/>Note
In this repository, we will release dataset and pytorch implementation of our paper.
Quick Start
Python 3.6+, Pytorch 1.2, torchvision 0.4, cuda10.0, and other requirements.
All codes are tested on Linux.
Installation
- Clone the repository
git clone https://github.com/TanJing94/Deep_Portraits_Correction.git cd Deep_Portraits_Correction
- Install dependencies
pip install -r requirements.txt
Resources preparation
- Dataset
- Download from [BaiduCloud], extraction code: 5pe5
- Please refer to [dataset.py] for data usage
- Pre-trained model
Training
Testing
Citation
If you find this work or code is helpful in your research, please cite:
@inproceedings{tan2021practical,
title={Practical Wide-Angle Portraits Correction with Deep Structured Models},
author={Tan, Jing and Zhao, Shan and Xiong, Pengfei and Liu, Jiangyu and Fan, Haoqiang and Liu, Shuaicheng},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={3498--3506},
year={2021}
}