Deep Residual Networks with a Fully Connected Recon-struction Layer for Single Image Super-Resolution

24 May 2018 Yongliang Tang Jiashui Huang Faen Zhang Weiguo Gong

Recently, deep neural networks have achieved impressive performance in terms of both reconstruction accuracy and efficiency for single image super-resolution (SISR). However, the network model of these methods is a fully convolutional neural network, which is limit to exploit the differentiated contextual information over the global region of the input image because of the weight sharing in convolution height and width extent... (read more)

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