论文标题
用于成像的多解决神经网络
Multiresolution Neural Networks for Imaging
论文作者
论文摘要
我们介绍MR-NET，这是一种用于多分辨率神经网络的通用体系结构，也是基于此体系结构进行成像应用的框架。我们基于坐标的网络在空间和规模上都是连续的，因为它们由多个阶段组成，这些阶段逐渐增加了更细节。除此之外，它们是一个紧凑而有效的表示。我们展示了多分辨率图像表示形式以及用于质地化，缩小和抗脉化的应用。该文档是论文[PNS+22]的扩展版本。它包括其他材料，这些材料不符合会议轨道出版的页面限制。
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 texturemagnification, minification, and antialiasing. This document is the extended version of the paper [PNS+22]. It includes additional material that would not fit the page limitations of the conference track for publication.
