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What is Pixel Recursive Super Resolution Model about?

1. The document presents a pixel recursive super resolution model that uses a PixelCNN architecture as a prior to generate realistic high resolution images from low resolution inputs. 2. It combines a conditioning network, consisting of ResNet blocks, with the PixelCNN prior network to map low resolution images to distributions over plausible high resolution outputs. 3. Human evaluations found that samples from the proposed model look more photo realistic than baselines using L2 regression, which tend to

Author

PJF

Language

EN