- Notifications
You must be signed in to change notification settings - Fork6
Attention Guided Low-light Image Enhancement with a Large Scale Low-light Simulation Dataset, IJCV 2021.
License
NotificationsYou must be signed in to change notification settings
yu-li/AGLLNet
Folders and files
| Name | Name | Last commit message | Last commit date | |
|---|---|---|---|---|
Repository files navigation
This is the test code for “Attention Guided Low-light Image Enhancement with a Large Scale Low-light Simulation Dataset” in IJCV 2021, byFeifan Lv,Yu Li, andFeng Lu.
Paper |ArXiv |Project page (data)
python 3.5
Tensorflow 1.6.0
Keras 2.2.0
imageio
opencv
You can put you image into the folderinput and run
cd AGLLNetpython run_agllnet.pyThe results will be stored in the folderoutput.
Training code willNOT be provided this time.
- AgLLNet.h5 (This model is newly trained for general low light enhancement. It is not strictly the one used in our IJCV paper).
If you use this code for your research, please consider star this repo and cite our paper.
@article{lv2021attention, title={Attention guided low-light image enhancement with a large scale low-light simulation dataset}, author={Lv, Feifan and Li, Yu and Lu, Feng}, journal={International Journal of Computer Vision}, volume={129}, number={7}, pages={2175--2193}, year={2021}}Learning Temporal Consistency for Low Light Video Enhancement from Single Images (CVPR2021)Paper |Code