FG-SRGAN: A Feature-Guided Super-Resolution Generative Adversarial Network for Unpaired Image Super-Resolution

Shuailong Lian; Zhou Hejian; Yi Sun

doi:10.1007/978-3-030-22796-8_17

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FG-SRGAN: A Feature-Guided Super-Resolution Generative Adversarial Network for Unpaired Image Super-Resolution

Shuailong Lian Zhou Hejian Yi Sun

Year: 2019 Lecture notes in computer science Pages: 151-161 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-030-22796-8_17

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Keywords:

Computer science Artificial intelligence Feature (linguistics) Resolution (logic) Image (mathematics) Computer vision Convolution (computer science) Domain (mathematical analysis) Bicubic interpolation Image resolution Convolutional neural network Low resolution Pattern recognition (psychology) Artificial neural network High resolution Mathematics

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Advanced Image Processing Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Image and Signal Denoising Methods

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Advanced Vision and Imaging

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

FG-SRGAN: A Feature-Guided Super-Resolution Generative Adversarial Network for Unpaired Image Super-Resolution

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