Event Camera Demosaicing via Swin Transformer and Pixel-focus Loss

Overview

This repository contains the official implementation of our paper "Event Camera Demosaicing via Swin Transformer and Pixel-focus Loss," accepted at the CVPR Workshop 2024. Our work introduces a novel approach to demosaicing for event cameras using Swin Transformers coupled with a pixel-focus loss mechanism, significantly enhancing image reconstruction quality.

Citation

If you find our work useful in your research, please consider citing:

@inproceedings{yourname2024event,
  title={Event Camera Demosaicing via Swin Transformer and Pixel-focus Loss},
  author={Yunfan Lu, Yijie Xu, Wenzong Ma, Weiyu Guo, Hui Xiong},
  booktitle={CVPR Workshop},
  year={2024}
}

Installation

Requirements

python 3.8+
torch 1.8.0+
torchvision 0.9.0+

Other dependencies listed in requirements.txt

Setup

Clone the repository and install the dependencies:

git clone https://github.com/yunfanLu/ev-demosaic.git
pip install -r requirements.txt

Dataset

To train the model

python train.py --config configs/train_config.yaml

To evaluate the model

python evaluate.py --config configs/eval_config.yaml --model_path /path/to/model.pth

Pre-trained Models

Link to any pre-trained models you are providing, and instructions on how to use them.

Acknowledgments

Thanks to these open source projects, which are vital for our proejct.

• VRT: https://github.com/JingyunLiang/VRT
• RSTT: https://github.com/llmpass/RSTT
• SwinIR: https://github.com/JingyunLiang/SwinIR