PixelCNN

2000년 도입 · 논문 45편에서 사용

A PixelCNN is a generative model that uses autoregressive connections to model images pixel by pixel, decomposing the joint image distribution as a product of conditionals. PixelCNNs are much faster to train than PixelRNNs because convolutions are inherently easier to parallelize; given the vast number of pixels present in large image datasets this is an important advantage.

출처: Pixel Recurrent Neural Networks

소개 논문: Pixel Recurrent Neural Networks