Image super-resolution (SR) techniques reconstruct a higher-resolution (HR) image or sequence from the observed lower-resolution (LR) images, e.g. upscaling of 720p image into 1080p.
One of the common approaches to solving this task is to use deep convolutional neural networks capable of recovering HR images from LR ones. And ESRGAN (Enhanced SRGAN) is one of them.
ESRGAN achieves consistently better visual quality with more realistic and natural textures than SRGAN.
Access colab file at : ESRGAN.ipynb
This notebook is a simple implementation of the paper "ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks"
Read the paper here: ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks