Fast and Efficient Image Quality Enhancement via Desubpixel Convolutional Neural Networks

ECCV2018 2018 Thang VuCao V. NguyenTrung X. PhamTung M. LuuChang D. Yoo

This paper considers a convolutional neural network for image quality enhancement referred to as the fast and efficient quality enhancement (FEQE) that can be trained for either image super-resolution or image enhancement to provide accurate yet visually pleasing images on mobile devices by addressing the following three main issues. First, the considered FEQE performs majority of its computation in a lowresolution space... (read more)

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