Lightweight interactive feature inference network for single-image super-resolution

Lightweight interactive feature inference network for single-image super-resolution

Abstract The emergence of convolutional neural network (CNN) and transformer has recently facilitated significant advances in image super-resolution (SR) tasks. However, these networks commonly construct complex structures, having huge model parameters and high computational costs, to boost reconstr...

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Bibliographic Details
Main Authors: Li Wang, Xing Li, Wei Tian, Jianhua Peng, Rui Chen
Format: Article
Language:English
Published: Nature Portfolio 2024-05-01
Series:Scientific Reports
Subjects:
Super-resolution
Convolution neural network
Transformer
Local and global priors
Online Access:https://doi.org/10.1038/s41598-024-62633-8
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https://doi.org/10.1038/s41598-024-62633-8

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