Deep Hierarchical Super Resolution for Scientific Data. (arXiv:2107.00462v2 [eess.IV] UPDATED)

We present a novel technique for hierarchical super resolution (SR) with
neural networks (NNs), which upscales volumetric data represented with an
octree data structure to a high-resolution uniform grid with minimal seam
artifacts on octree node boundaries. Our method uses existing state-of-the-art
SR models and adds flexibility to upscale input data with varying levels of
detail across the domain, instead of only uniform grid data that are supported
in previous approaches. The key is to use a hierarchy of SR …

arxiv data hierarchical super resolution