SRTGAN: Triplet Loss based Generative Adversarial Network for Real-World Super-Resolution. (arXiv:2211.12180v1 [eess.IV])

Many applications such as forensics, surveillance, satellite imaging, medical
imaging, etc., demand High-Resolution (HR) images. However, obtaining an HR
image is not always possible due to the limitations of optical sensors and
their costs. An alternative solution called Single Image Super-Resolution
(SISR) is a software-driven approach that aims to take a Low-Resolution (LR)
image and obtain the HR image. Most supervised SISR solutions use ground truth
HR image as a target and do not include the information provided in the …

arxiv generative adversarial network loss network