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Found 2 papers, 2 papers with code
Boosting Flow-based Generative Super-Resolution Models via Learned Prior
This prior is a latent code predicted by our proposed latent module conditioned on the low-resolution image, which is then transformed by the flow model into an SR image.
Ranked #3 on
Image Super-Resolution
on DIV2K val - 4x upscaling
(using extra training data)
Local Implicit Normalizing Flow for Arbitrary-Scale Image Super-Resolution
Flow-based methods have demonstrated promising results in addressing the ill-posed nature of super-resolution (SR) by learning the distribution of high-resolution (HR) images with the normalizing flow.
Ranked #5 on
Image Super-Resolution
on DIV2K val - 4x upscaling
(using extra training data)
