Super-resolutionMulti-view information fusionLightweight networkIn recent years, convolution neural networks (CNN) have achieved substantial advantages for single image super resolution (SISR). However, as the depth and width of the networks increase, the model parameters and computation become more ...
In this paper, we introduce the medium transmission (MT) maps to advance super-resolution tasks for underwater images. A multi-view network is designed to fuse information from the original underwater images and the MT maps, which provides information on the underlying physical properties of the...
期刊名称:Journal of Visual Communication and Image Representation 论文地址:Multi-scale attention network for image super-resolution - ScienceDirectWang、Xiaoguang Liu 单位:南开-百度联合实验室,中国南开大 研究动机动机源于卷积神经网络(CNN)在高级计算机视觉任务中与基于变换器的方法竞争时存在的局限性,尤其是在...
【图像超分辨率】Multi-scale Residual Network for Image Super-Resolution,程序员大本营,技术文章内容聚合第一站。
There is growing demand for accuracy in image processing and visualization, and the super-resolution (SR) technique for multi-observed RGB-D images has become popular, because it provides space-redundant information and produces a detailed reconstruction even with a large magnification factor. This te...
【图像超分辨率】Single image super-resolution using multi-scale feature enhancement attention residual net,程序员大本营,技术文章内容聚合第一站。
Sparse representation provides a new method of generating a super-resolution image from a single low resolution input image. An over-complete base for sparse representation is an essential part of such methods. However, discovering the over-complete base with efficient representation from a large amou...
Multi frame image super resolution. Contribute to wanyueli/Multi-frame-image-super-resolution development by creating an account on GitHub.
The super-resolution reconstruction (SR) has become the critical aspect in researches about image processing and computer vision, and widely applied in traffic monitoring, remote sensing, live recording, etc. [[1], [2], [3], [4]]. Based on the number of available LR observations, SR algor...
基于支撑帧和参考帧的对齐特征,进行融合操作,将所有特征聚合成整个时间序列的整体特征表示,然后作为输入用于重建 HR 帧。 回到顶部 问题: 主要问题是特征融合操作没有考虑融合特征与原始 LR 参考帧中的视觉信息之间的差异。 这种差异可能是由于视频中的强烈运动导致的不完美的特征对齐或严重模糊造成的, ...