Masked Convolution
Masked Convolution
A **Masked Convolution** is a type of [convolution](https://paperswithcode.com/method/convolution) which masks certain pixels so that the model can only predict based on pixels already seen. This type of convolution was introduced with [PixelRNN](https://paperswithcode.com/method/pixelrnn) generative models, where an image is generated pixel by pixel, to ensure that the model was conditional only on pixels already visited.
Pixel Recurrent Neural Networks
https://paperswithcode.com/paper/pixel-recurrent-neural-networks
Pixel Recurrent Neural Networks