CVPR 2024 真实超分 SeeSR: Towards Semantics-Aware Real-World Image Super-Resolution 星晴 AIGC72 人赞同了该文章 arxiv:arxiv.org/pdf/2311.1651 港理工张磊的又一个新作,将包含语义信息的Prompts用于真实超分 Motivation 由于退化会导致局部结构的破坏和语义信息的模糊,text-to-image (T2I) diffusion models...
[2]https://blog.csdn.net/qq_27825451/article/details/102954096 [3] Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-Resolution
首先训练基于GAN的下采样网络DSN,将HR下采样到real-world domain,同时生成Domain Distance Map unpaired数据如果用 容易产生图像伪影,并且可能难以收敛,因此在DSN中仅仅只将高频信息输入判别器,因为图像的噪声退化主要集中在高频信息 为了避免冗余信息的影响,让判别器判别的特征更加明确,作者采用高频判别的方式训练在训练阶...
Recent deep learning based single image super-resolution (SISR) methods mostly train their models in a clean data domain where the low-resolution (LR) and the high-resolution (HR) images come from noise-free settings (same domain) due to the bicubic down-sampling assumption. However, such deg...
We show that it is possible to form real, super-resolution images using high-refractive index microspheres. Also, we report on how changes to a microsphere's refractive index and size affect image formation and planes. The relationship between the focus position and the additional magnification ...
超分辨率(Super-Resolution)指通过硬件或软件的方法提高原有图像的分辨率,通过一系列低分辨率的图像来得到一幅高分辨率的图像过程。通俗的说就是在保持原图像清晰度不变的前提下,将图像放大。使用深度学习模型进行超分已经是比较常用的手段,而且深度学习模型又一个好处,可以在数据增强的时候对数据进行退化处理,在超分的...
The image real-time super-resolution reconstruction method based on the acceleration of the GPU mainly solves the problem that an existing high quality image super-resolution reconstruction serial algorithm is hard to process in real time. The method comprises the following steps of (1) inputting ...
In this paper, we present D2C-SR, a novel framework for the task of real-world image super-resolution. As an ill-posed problem, the key challenge in super-resolution related tasks is there can be multiple predictions for a given low-resolution input. Most classical deep learning based approa...
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network 摘要 近年来,基于深度神经网络的几种模型在单幅图像超分辨率重建精度和计算性能方面都取得了很大的成功。在这些方法中,通常在重建之前,使用单个滤波器(通常为双三次插值)将低分辨率(LR)输入图像放大到高分...
Recently, several models based on deep neural networks have achieved great success in terms of both reconstruction accuracy and computational performance for single image super-resolution. In these methods, the low resolution (LR) input image is upscaled to the high resolution (HR) space using a ...