Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling

@article{Liang2021HierarchicalCF,
  title={Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling},
  author={Jingyun Liang and Andreas Lugmayr and K. Zhang and Martin Danelljan and Luc Van Gool and Radu Timofte},
  journal={2021 IEEE/CVF International Conference on Computer Vision (ICCV)},
  year={2021},
  pages={4056-4065}
}
Normalizing flows have recently demonstrated promising results for low-level vision tasks. For image super-resolution (SR), it learns to predict diverse photo-realistic high-resolution (HR) images from the low-resolution (LR) image rather than learning a deterministic mapping. For image rescaling, it achieves high accuracy by jointly modelling the downscaling and upscaling processes. While existing approaches employ specialized techniques for these two tasks, we set out to unify them in a… 

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