Noise2Fast
Noise2Fast
**Noise2Fast** is a model for single image blind denoising. It is similar to masking based methods -- filling in the pixel gaps -- in that the network is blind to many of the input pixels during training. The method is inspired by Neighbor2Neighbor, where the neural network learns a mapping between adjacent pixels. Noise2Fast is tuned to speed by using a discrete four image training set obtained by a form of downsampling called “checkerboard downsampling.
Noise2Fast: Fast Self-Supervised Single Image Blind Denoising
https://paperswithcode.com/paper/noise2fast-fast-self-supervised-single-image
Noise2Fast: Fast Self-Supervised Single Image Blind Denoising