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.
Source: Noise2Fast: Fast Self-Supervised Single Image Blind DenoisingPaper | Code | Results | Date | Stars |
---|
Component | Type |
|
---|---|---|
🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |