45 citations · 117 across the 22 of their papers we have counts for
8 papers · 1 filter
MAR-DTN: Metal Artifact Reduction using Domain Transformation Network for Radiotherapy Planning
Belén Serrano-Antón, Mubashara Rehman, Niki Martinel +5
For the planning of radiotherapy treatments for head and neck cancers, Computed Tomography (CT) scans of the patients are typically employed. However, in patients with head and nec…
A Deep Residual Star Generative Adversarial Network for multi-domain Image Super-Resolution
Rao Muhammad Umer, Asad Munir, Christian Micheloni
Recently, most of state-of-the-art single image super-resolution (SISR) methods have attained impressive performance by using deep convolutional neural networks (DCNNs). The existi…
AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results
Kai Zhang, Martin Danelljan, Yawei Li +75
This paper reviews the AIM 2020 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The challenge task was to super-resolve an in…
Deep Iterative Residual Convolutional Network for Single Image Super-Resolution
Rao Muhammad Umer, Gian Luca Foresti, Christian Micheloni
Deep convolutional neural networks (CNNs) have recently achieved great success for single image super-resolution (SISR) task due to their powerful feature representation capabiliti…
Deep Cyclic Generative Adversarial Residual Convolutional Networks for Real Image Super-Resolution
Rao Muhammad Umer, Christian Micheloni
Recent deep learning based single image super-resolution (SISR) methods mostly train their models in a clean data domain where the low-resolution (LR) and the high-resolution (HR)…
NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results
Andreas Lugmayr, Martin Danelljan, Radu Timofte +43
This paper reviews the NTIRE 2020 challenge on real world super-resolution. It focuses on the participating methods and final results. The challenge addresses the real world settin…