设图像I有对应的2D特征图M∈R^(H*W*D),定义local implicit image function(LIIF)为f: 其中,s为输出的RGB值,θ为f的参数,z为M中的特征向量,x为所查询位置的2D坐标。 因此,根据f,对任意位置x_q,其重构的RGB 值为: 其中,z*为离x_q最近的特征向量,v*为z*对应的坐标。上式记为(1)式。 2)特征...
Learning Continuous Image Representation with Local Implicit Image Function(阅读笔记)11.03 局部隐式图像函数(LIIF)表示连续中的图像,可以以任意高分辨率表示。 摘要:如何表示图像?当视觉世界以连续的方式呈现时,机器用二维像素数组以离散的方式存储和观看图像。本文中,试图学习图像的连续表示。受隐式神经表示在三维重建...
基于此,本文提出Local Implicit Image Function,LIIF,它将图像表示为一系列空间分布的隐变量。给定任意坐标,LIIF通过局部隐变量以及坐标来解码得到图像的像素值。由于坐标是连续的,因此LIIF可以适应任意分辨率。 In this paper, we propose the Local Implicit Image Function (LIIF) for representing natural and complex...
目前使用encoder-based方法的implicit function无法表示高保真图像,这可能是由于只用一个简单的latent code完全encode图像的所有细节比较困难。 因此本文提出用一组encode来表示一个图像,即Local Implicit Image Function(LIIF) 具体来说就是,对于给定的坐标,根据坐标信息查询该坐标附近的局部latent codes作为函数输入,预测其R...
Learning Continuous Image Representation with Local Implicit Image Function Yinbo Chen,Sifei Liu,Xiaolong Wang CVPR 2021 (Oral) The project page with video is athttps://yinboc.github.io/liif/. Citation If you find our work useful in your research, please cite: ...
Local Implicit Normalizing Flow for Arbitrary-Scale Image Super-Resolution Jie-En Yao⇤1, Li-Yuan Tsao⇤1, Yi-Chen Lo†2, Roy Tseng†2, Chia-Che Chang†2, and Chun-Yi Lee1 1ElsaLab, National Tsing Hua University, 2MediaTek Inc. {matt1129yao, ...
Subsequently, fine-tuning on a single clean image enables denoising noisy images. Unlike Noise2Score, which relies on Tweedie’s formula, our method introduces a lightweight decoder based on Local Implicit Image Function (LIIF) for per-pixel noise adjustment and clean image reconstruction. ...
Projects Security Insights Additional navigation options main 1Branch0Tags Code README BSD-3-Clause license This repository contains the official implementation for LTE introduced in the following paper: Local Texture Estimator for Implicit Representation Function(CVPR 2022) ...
Chen, Y.; Liu, S.; Wang, X. Learning continuous image representation with local implicit image function. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Nashville, TN, USA, 20–25 June 2021; pp. 8628–8638. [Google Scholar] ...