Fast and Accurate Single Image Super-Resolution via Information Distillation Network
本文主旨为了再生成深度网络的同时降低计算复杂性和减少内存消耗，因此本文提出了一个信息蒸馏网络，降低复杂性和内存消耗。 总体网络框架分为三个部分①特征提取模块②增强模块（蒸馏模块）③特征融合与生成图片模块 总体来说首先低分辨率图片输入到网络中经过双三次插值放大到指定大小输入后层形成残差网络，后低分辨率图片首先经过FBLOCK提取浅层特征，后经过DBLOCK经过信息蒸馏再提取深层特征的同时减少内存消耗
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相关文章
- 1. PaperNote-Fast and Accurate Single Image Super-Resolution via Information Distillation Network
- 2. IDN-Fast and Accurate Single Image Super-Resolution via Information Distillation Network信息蒸馏网络
- 3. 【论文笔记2_超分辨】（IDN）Fast and Accurate Single Image Super-Resolution via Information Distillation Network
- 4. 文献阅读:Fast and Accurate Single Image Super-Resolution via Information Distillation N (IDN CVPR2018)
- 5. Deep Neural Network for Fast and Accurate Single Image Super-Resolution via Channel-Attention-based
- 6. 文献阅读:Lightweight Image Super-Resolution with Information Multi-distillation Network (ACMM2019)
- 7. 论文阅读：Fast Single Image Rain Removal via a Deep Decomposition-Composition Network
- 8. Single Image Dehazing via Conditional Generative Adversarial Network
- 9. Semantic Flow for Fast and Accurate Scene Parsing
- 10. PEPSI++: Fast and Lightweight Network for Image Inpainting | 简记