167 citations · 188 across the 4 of their papers we have counts for
4 papers
A General Method to Incorporate Spatial Information into Loss Functions for GAN-based Super-resolution Models
Xijun Wang, Santiago López-Tapia, Alice Lucas +3
Generative Adversarial Networks (GANs) have shown great performance on super-resolution problems since they can generate more visually realistic images and video frames. However, t…
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…
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…
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…