BriefGPT.xyz
Jul, 2023
DDGM: 基于扩散去噪的梯度最小化求解反问题
DDGM: Solving inverse problems by Diffusive Denoising of Gradient-based Minimization
HTML
PDF
Kyle Luther, H. Sebastian Seung
TL;DR
该论文提出了一种基于梯度下降与降噪相结合的噪声重建方法,可以高精度地重建电子显微学的层析成像问题,结果表明相对于传统方法和更复杂的扩散方法,该方法具有更高的精度和更快的计算速度。
Abstract
inverse problems
generally require a regularizer or prior for a good solution. A recent trend is to train a
convolutional net
to denoise images, and use this net as a prior when solving the inverse problem. Sever
→