1520-9210 (c) 2016 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TMM.2017.2711263, IEEE Transactions on Multimedia IEEE TRANSACTIONS ON MULTIMEDIA 1 Structure-Preserving Image Super-resolution via Contextualized Multi-task Learning Yukai Shi, Keze Wang, Chongyu Chen, Li Xu, and Liang Lin Abstract—Single image super resolution (SR), which refers to reconstruct a higher-resolution (HR) image from the observed low-resolution (LR) image, has received substantial attention due to its tremendous application potentials. Despite the breakthroughs of recently proposed SR methods using convolutional neural networks (CNNs), their generated results us
