Unified Dynamic Convolutional Network for Super-Resolution with Variational Degradations
这篇文章首先介绍了现有现有超分网络大多通过利用HR图像直接进行双三次插值下采样得到LR图像来构成数据集，但使用这种方式构造出的数据集训练出的网络，对真实世界的含模糊核和噪声的低分辨率图片，泛化能力较差，生成的HR图像质量不佳，因此人们又提出在下采样构造lr图像的同时引入模糊核和噪声，但这种方式构造的数据集训练的网络也只能泛化几种模糊核和噪声的组合仍无法泛化真实世界的图片， Learning a S
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相关文章
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