Awesome
Coherent Event Guided Low-Light Video Enhancement
Jinxiu Liang<sup>1</sup>, Yixin Yang<sup>1</sup>, Boyu Li<sup>1</sup>, Peiqi Duan<sup>1</sup>, Yong Xu<sup>2</sup>, Boxin Shi<sup>1</sup>
<sup>1</sup>Peking University<br><sup>2</sup>South China University of Technology
<p align="center"> <img src="docs/static/images/teaser.jpg"> </p><p align="center"> <img src="docs/static/images/method-v8.jpg"> </p>
:star:If EvLowLight is helpful for you, please help star this repo. Thanks!:hugs:
Table Of Contents
<a name="todo"></a>TODO
- Release inference code and pretrained models.
- Update links to paper and project page.
- Provide a runtime environment Docker image.
- Release train code and training set.
<a name="installation"></a>Installation
-
Clone this repo using
git
:git clone https://github.com/sherrycattt/EvLowLight.git
-
Create environment:
Option 1: Using
pip
cd EvLowLight conda create -n evlowlight python=3.8 conda activate evlowlight pip install -r requirements.txt
Option 2: Using
docker
docker run --runtime=nvidia --gpus all --ipc=host --network=host --rm -it \ --ulimit memlock=-1 --ulimit stack=67108864 \ -v `pwd`/EvLowLight:/workspace \ -v `pwd`/timelens:/datasets/timelens \ sherrycat/evlowlight
Note the installation is only compatible with Linux users.
<a name="inference"></a>Inference
We provide an example for inference, check options/**_option.yml for more arguments.
python inference.py -opt options/timelens_option.yml
<a name="data"></a>Data Preparation
We provide example test data converted from the TimeLens for demo, which can be downloaded from Link (extracted code: Y9CN).
Please place the dataset in the ../datasets
folder. The dataset structure should be organized as follows:
├── timelens
│ └── events
│ ├── paprika_1000_gain_control_02
│ │ ├── events.txt
│ │ └── timestamp.txt
│ ├── pen_03
│ │ ├── events.txt
│ │ └── timestamp.txt
│ ...
│ └── low
│ ├── paprika_1000_gain_control_02
│ │ ├── 000000.png
│ │ └── 000001.png
│ │ ...
│ ├── pen_03
│ │ ├── 000000.png
│ │ └── 000001.png
│ │ ...
│ ...
│ ...
Each subfolder in the low
folder contains image files with template filename %06d.png
, and the file in the events
subfolder contains events corresponding to the image subfolder with template filename events.txt
defined as ev_file_ext
in the option configuration file.
Moreover, events
also contains timestamp.txt
where image timestamps are stored. The image stamps in timestamp.txt
should match with the image files .
Citation
Please cite us if our work is useful for your research.
@inproceedings{liang2023evlowlight,
title = {Coherent Event Guided Low-Light Video Enhancement},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
author = {Liang, Jinxiu and Yang, Yixin and Li, Boyu and Duan, Peiqi and Xu, Yong and Shi, Boxin},
year = {2023},
pages = {10615--10625},
}
License
This project is released under the Apache 2.0 license.
Acknowledgement
This project is based on BasicSR. Thanks for their awesome work.
Contact
If you have any questions, please feel free to contact with me at cssherryliang@pku.edu.cn
.