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PLKSR: Partial Large Kernel CNNs for Efficient Super-Resolution


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This repository is an official implementation of the paper "Partial Large Kernel CNNs for Efficient Super-Resolution", Arxiv, 2024.

by Dongheon Lee, Seokju Yun, and Youngmin Ro

[paper] [pretrained models]

Updates

Installation

git clone https://github.com/dslisleedh/PLKSR.git
cd PLKSR
conda create -n plksr python=3.10
conda activate plksr
conda install pytorch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 pytorch-cuda=12.1 -c pytorch -c nvidia
pip install -r requirements.txt
python setup.py develop

Train

python plksr/train.py -opt=$CONFIG_PATH

Test

python plksr/test.py -opt=$CONFIG_PATH

Results

<details> <summary>Quantitative Results</summary>

Main model

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Tiny model

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</details> <details> <summary>Visual Results</summary>

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</details>

Acknowledgement

This work is released under the MIT license. The codes are based on BasicSR. Thanks for their awesome works.

Contact

If you have any questions, please contact dslisleedh@gmail.com