Noise2One

[ICASSP'24] Noise2One: One-Shot Image Denoising with Local Implicit Learning

Authors: Kwanyoung Kim, Jong Chul Ye

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News

• [2024.07.29] Our official Code Release
• [2024.04.14] Our paper is accepted on ICASSP2024.

Environment:

• Install pytorch

conda install pytorch==1.10.1 torchvision==0.11.2 torchaudio=0.10.1 cudatoolkit=10.2 -c pytorch

• Install required packages.

pip install -r requirements.txt

Pretrained Score Model:

Dataset	Pretrained model zoo
Gaussian	[Google Drive]
Poisson	[Google Drive]

Validation Datset:

Dataset	dataset download link
CBSD300	[Google Drive]
Kodak24	[Google Drive]
Set14	[Google Drive]

Few-Shot Datset:

Dataset	dataset download link
One-Shot	[Google Drive]

Training (Inductive):

`bash demo_kan.sh`

Inference:

bash demo_kan.sh

Citation:

@inproceedings{kim2024noise2one,
  title={Noise2one: One-Shot Image Denoising with Local Implicit Learning},
  author={Kim, Kwanyoung and Ye, Jong Chul},
  booktitle={ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={13036--13040},
  year={2024},
  organization={IEEE}
}