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Topic: Advanced Image Processing Techniques ×Clear all

2 claims from 1 paper

1. Computer Science › Advanced Image Processing Techniques

   Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

   Ledig, Theis, Huszár et al. · arXiv (Cornell University) · 2016

   The paper presents SRGAN, a generative adversarial network for single image super-resolution that aims to recover realistic textures at 4x upscaling, and reports better perceptual quality in a rating test.

   Unchecked2 claims
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   1. UncheckedThe authors say SRGAN is, to their knowledge, the first framework able to infer photo-realistic natural images when enlarging images four times.“To our knowledge, it is the first framework capable of inferring photo-realistic natural images for 4x upscaling factors.”
   2. UncheckedThe authors' deep residual network can recover photo-realistic textures from heavily downsampled images on public benchmark datasets.“Our deep residual network is able to recover photo-realistic textures from heavily downsampled images on public benchmarks.”