3 papers
eess.IV2019
Self-supervised Fine-tuning for Correcting Super-Resolution Convolutional Neural Networks
Alice Lucas, Santiago Lopez-Tapia, Rafael Molina +1
While Convolutional Neural Networks (CNNs) trained for image and video super-resolution (SR) regularly achieve new state-of-the-art performance, they also suffer from significant d…
cs.CV2019
A Single Video Super-Resolution GAN for Multiple Downsampling Operators based on Pseudo-Inverse Image Formation Models
Santiago López-Tapia, Alice Lucas, Rafael Molina +1
The popularity of high and ultra-high definition displays has led to the need for methods to improve the quality of videos already obtained at much lower resolutions. Current Video…
cs.CV2018
Generative Adversarial Networks and Perceptual Losses for Video Super-Resolution
Alice Lucas, Santiago Lopez Tapia, Rafael Molina +1
Video super-resolution (VSR) has become one of the most critical problems in video processing. In the deep learning literature, recent works have shown the benefits of using advers…