Second-Order Attention Network for Single Image Super-Resolution

Recently, deep convolutional neural networks (CNNs) have been widely explored in single image super-resolution (SISR) and obtained remarkable performance. However, most of the existing CNN-based SISR methods mainly focus on wider or deeper architecture design, neglecting to explore the feature corre...

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Bibliographic Details
Main Authors: Dai, Tao, Cai, Jianrui, Zhang, Yongbing, Xia, Shu-Tao, Zhang, Lei
Format: Conference Proceeding
Language:English
Subjects:
Computer architecture
Computer vision
Convolutional neural networks
Correlation
Deep Learning
Degradation
Low-level Vision
Measurement
Pattern recognition
Periodic structures
Superresolution
Visualization
Online Access:Request full text
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