A suite of heterogeneous models with diverse network structure and hyperparameter are selected for model-ensemble to achieve outstanding performance in real image SR. The proposed method won the first place in all three tracks of the AIM 2020 Real Image Super-Resolution Challenge....
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 在处理真实超分的时候会产生语义的错误,特别是当物体很多或者退化很严重的时候。那么这篇文章就是聚焦于如何提取效果更好的semantic prompts。 作者提出了两条标准: prompts要覆盖尽可能多的物体,这样DM才可以更好地理解LR不同区...
本来想要分享我们ICCV2023的新工作<Towards Real-world Burst Image Super-Resolution: Benchmark and Method>(2023.10.26更新,新工作的链接子不语:ICCV2023|迈向真实世界的多帧超分),但是发现很少有人分享目前的超分领域的real-world这个子方向,所以干脆先抛砖引玉。 目前的超分,如果根据数据获取的来源,大概可以分为...
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...
【文字超分辨率】Real-time Document Image Super-Resolution by Fast Matting 阅读笔记,程序员大本营,技术文章内容聚合第一站。
Unsupervised Real-world Image Super Resolution via Domain-distance Aware Training,参考:https://www.bilibili.com/video/BV1PT4y1d7b4Bicubic的方法无
SeeSR: Towards Semantics-Aware Real-World Image Super-Resolution (CVPR2024) Rongyuan Wu1,2|Tao Yang3|Lingchen Sun1,2|Zhengqiang Zhang1,2|Shuai Li1,2|Lei Zhang1,2 1The Hong Kong Polytechnic University,2OPPO Research Institute,3ByteDance Inc. ...
Deeply-Recursive Convolutional Network (DRCN) for Image Super-Resolution Photo-Realistic Super-Resolution Using a Generative Adversarial Network 本文以第三篇文章为例,来介绍该项目超分辨率算法的基本实现思路。目前的超分辨率算法,主攻的方向还是高频信息的恢复。而DRCN通过一个加深了层数的卷积网络,来实现对高频信...
Real-ESRGAN 的目标是开发出实用的图像/视频修复算法。 我们在 ESRGAN 的基础上使用纯合成的数据来进行训练,以使其能被应用于实际的图片修复的场景(顾名思义:Real-ESRGAN)。 Real-ESRGAN的官方入口 官方GiHub项目库:https://github.com/xinntao/Real-ESRGAN ...
Come with it, an increasing number of attentions have been attracted by deep super-resolution (SR) approaches. Many existing methods attempt to restore high-resolution images from directly down-sampled low-resolution images or with the assumption of Gaussian degradation kernels with additive noises ...