Multiresolution Neural Networks for Imaging

  • Hallison Paz IMPA
  • Tiago Novello IMPA
  • Vinicius Silva PUC-Rio
  • Guilherme Schardong Universidade de Coimbra
  • Luiz Schirmer Universidade de Coimbra
  • Fabio Chagas IMPA
  • Helio Lopes PUC-Rio
  • Luiz Velho IMPA


We present MR-Net, a general architecture for multiresolution neural networks, and a framework for imaging applications based on this architecture. Our coordinate-based networks are continuous both in space and in scale as they are composed of multiple stages that progressively add finer details. Besides that, they are a compact and efficient representation. We show examples of multiresolution image representation and applications to texture magnification, minification, and antialiasing.
Palavras-chave: Graphics, Image resolution, Neural networks, Imaging, Image representation, Multiresolution, Level fo Detail, Neural Networks, Textures
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PAZ, Hallison; NOVELLO, Tiago; SILVA, Vinicius; SCHARDONG, Guilherme; SCHIRMER, Luiz; CHAGAS, Fabio; LOPES, Helio; VELHO, Luiz. Multiresolution Neural Networks for Imaging. In: CONFERENCE ON GRAPHICS, PATTERNS AND IMAGES (SIBGRAPI), 35. , 2022, Natal/RN. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2022 .