Awesome
Deep Fourier-based Exposure Correction with Spatial-Frequency Interaction (ECCV 2022)
Jie Huang+, Yajing Liu+, Feng Zhao*, Keyu Yan, Jinghao Zhang, Yukun Huang, Man Zhou, Zhiwei Xiong
*Equal Corresponding Authors
+Equal Contributions
University of Science and Technology of China (USTC)
Introduction
This repository is the official implementation of the paper, "Deep Fourier-based Exposure Correction with Spatial-Frequency Interaction", where more implementation details are presented.
0. Hyper-Parameters setting
Overall, most parameters can be set in options/train/train_Enhance.yml
1. Dataset Preparation
Create a .txt file to put the path of the dataset using
python create_txt.py
2. Training
python train.py --opt options/train/train_Enhance.yml
3. Inference
set is_training in "options/train/train_Enhance.yml" as False set the val:filelist as the validation set.
then
python train.py --opt options/train/train_Enhance.yml
Dataset
MSEC dataset (please refer to https://github.com/mahmoudnafifi/Exposure_Correction)
SICE dataset (I have uploaded it to https://share.weiyun.com/C2aJ1Cti)
Ours Results
MSEC dataset (https://drive.google.com/file/d/1AOuWujPffYaYJsDmkA8OcyU5S5a4zClP/view?usp=drive_link)
SICE dataset (https://drive.google.com/file/d/1_Ya8iyRqOGoOy10nAyTHZS-6dJcuLVhU/view?usp=drive_link)
Contact
If you have any problem with the released code, please do not hesitate to contact me by email (hj0117@mail.ustc.edu.cn).
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