论文阅读：Removing rain from single images via a deep detail network
之前的概述所包含的文章内容主要包括了视频的去雨，以及基于传统方法（像核回归非局部均值滤波、低秩矩阵、基于Patch的建模、判别稀疏编码、GMM层先验等等）的单幅图像去雨。 从这篇往后会认真看去雨的网络方法。 1、2017CVPR ： DDN 这篇文章主要基于深度卷积神经网络以及ResNet，提出了一种深度细节网络用于减少从输入到输出的映射范围，使得学习过程更简单。 同时使用先验图像域知识，在训练中
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相关文章
- 1. 论文阅读：Fast Single Image Rain Removal via a Deep Decomposition-Composition Network
- 2. 【论文解读】深度残差网络去雨模型cvpr_Removing rain from single images via a deep detail network
- 3. 【论文阅读】Clearing the Skies: A deep network architecture for single-image rain removal
- 4. 【论文阅读】Deep Joint Rain Detection and Removal from a Single Image
- 5. 论文阅读：Clearing the Skies: A Deep Network Architecture for Single-Image Rain Removal
- 6. 论文阅读：Deep Joint Rain Detection and Removal from a Single Image
- 7. A Model-driven Deep Neural Network for Single Image Rain Removal阅读分享
- 8. DEX: Deep EXpectation of apparent age from a single image 论文阅读
- 9. 论文阅读：Rain Streak Removal for Single Image via Kernel Guided CNN
- 10. 论文阅读笔记----HDR image reconstruction from a single exposure using deep CNNs