Multiresolution Neural Networks for Imaging
ResumoWe 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
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 .