論文閱讀：Removing rain from single images via a deep detail network
之前的概述所包含的文章內容主要包括了視頻的去雨，以及基於傳統方法（像核迴歸非局部均值濾波、低秩矩陣、基於Patch的建模、判別稀疏編碼、GMM層先驗等等）的單幅圖像去雨。 從這篇往後會認真看去雨的網絡方法。 1、2017CVPR ： DDN 這篇文章主要基於深度卷積神經網絡以及ResNet，提出了一種深度細節網絡用於減少從輸入到輸出的映射範圍，使得學習過程更簡單。 同時使用先驗圖像域知識，在訓練中
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相關文章
- 1. 論文閱讀：Fast Single Image Rain Removal via a Deep Decomposition-Composition Network
- 2. 【論文解讀】深度殘差網絡去雨模型cvpr_Removing rain from single images via a deep detail network
- 3. 【論文閱讀】Clearing the Skies: A deep network architecture for single-image rain removal
- 4. 【論文閱讀】Deep Joint Rain Detection and Removal from a Single Image
- 5. 論文閱讀：Clearing the Skies: A Deep Network Architecture for Single-Image Rain Removal
- 6. 論文閱讀：Deep Joint Rain Detection and Removal from a Single Image
- 7. A Model-driven Deep Neural Network for Single Image Rain Removal閱讀分享
- 8. DEX: Deep EXpectation of apparent age from a single image 論文閱讀
- 9. 論文閱讀：Rain Streak Removal for Single Image via Kernel Guided CNN
- 10. 論文閱讀筆記----HDR image reconstruction from a single exposure using deep CNNs