liuguoyou / kind

Kindling the Darkness: a Practical Low-light Image Enhancer

KinD

This is a Tensorflow implementation of KinD

Kindling the Darkness: a Practical Low-light Image Enhancer. In ACMMM2019
Yonghua Zhang, Jiawan Zhang, Xiaojie Guo

Requirements

1. Python
2. Tensorflow >= 1.10.0
3. numpy, PIL

Test

First download the pre-trained checkpoints from here, then just run

python evaluate.py

Train

Please download the LOLdataset. Save training pairs of LOL dataset under './LOLdataset/our485/' and save evaluating pairs under './LOLdataset/eval15/'. For training, just run

python decomposition_net_train.py
python adjustment_net_train.py
python reflectance_restoration_net_train.py

You can also evaluate on the LOLdataset, just run

python evaluate_LOLdataset.py

Our code partly refers to the code.

Citation

@inproceedings{zhang2019kindling,
 author = {Zhang, Yonghua and Zhang, Jiawan and Guo, Xiaojie},
 title = {Kindling the Darkness: A Practical Low-light Image Enhancer},
 booktitle = {Proceedings of the 27th ACM International Conference on Multimedia},
 series = {MM '19},
 year = {2019},
 isbn = {978-1-4503-6889-6},
 location = {Nice, France},
 pages = {1632--1640},
 numpages = {9},
 url = {http://doi.acm.org/10.1145/3343031.3350926},
 doi = {10.1145/3343031.3350926},
 acmid = {3350926},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {image decomposition, image restoration, low light enhancement},
}