Noise2Noise, unofficial PyTorch implementation

• Paper

This is a simple implementation of the Noise2Noise paper (Lehtinen et al., 2018).

Requirements

It requires torch, torchvision, numpy, matlplotlib and tqdm. It can be installed this way:

pip install -r requirements.txt

Data

I used 32x32 images from ImageNet with random gaussian noise. The images are available in the form of pickle files for PyTorch. Pretrained weights are also available on this Drive.

Use

A demo Jupyter Notebook is available here: .

Report

A full report on this implementation can be found here.