RCAN Image Super-Resolution Using Very Deep Residual Channel Attention Networks-ECCV2018
目录 一.提出问题： 二.解决问题方法： 三.贡献： 四.网络结构 五.Channel attention(CA) 六：结论 一.提出问题： 1.卷积神经网络深度对于图像超分辨率至关重要。然而，我们观察到更深层的图像SR网络更难以训练。 2.低分辨率输入和特征包含丰富的低频信息，平等对待你这些通道，阻碍了cnn代表。 二.解决问题方法： 为了解决这些问题，我们提出了非常深的残余信道注意网络（R
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相关文章
- 1. 《Image Super-Resolution Using Very Deep Residual Channel Attention Networks》
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- 4. SR文献学习之《Image Super-Resolution Using Very Deep Residual Channel Attention Networks》
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