FormResNet: Formatted residual learning for image restoration

• Main Authors: JIAO, Jianbo, TU, Wei-chih, HE, Shengfeng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2017
• Subjects: Computer vision; Deep learning; Deep neural networks; Pattern recognition; Restoration; Semantics; Artificial Intelligence and Robotics; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/8428; https://ink.library.smu.edu.sg/context/sis_research/article/9431/viewcontent/Jiao_FormResNet_Formatted_Residual_CVPR_2017_paper.pdf
• Institution: Singapore Management University

In this paper, we propose a deep CNN to tackle the image restoration problem by learning the structured residual. Previous deep learning based methods directly learn the mapping from corrupted images to clean images, and may suffer from the gradient exploding/vanishing problems of deep neural networ...