Likelihood-Based Generative Models

PixelCNN

Introduced by Oord et al. in Conditional Image Generation with PixelCNN Decoders

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.

Source: Conditional Image Generation with PixelCNN Decoders

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🤖 No Components Found You can add them if they exist; e.g. Mask R-CNN uses RoIAlign

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