Search Results for author: Rao Muhammad Umer

Found 10 papers, 6 papers with code

RBSRICNN: Raw Burst Super-Resolution through Iterative Convolutional Neural Network

1 code implementation25 Oct 2021 Rao Muhammad Umer, Christian Micheloni

Modern digital cameras and smartphones mostly rely on image signal processing (ISP) pipelines to produce realistic colored RGB images.

Image Super-Resolution

A Deep Residual Star Generative Adversarial Network for multi-domain Image Super-Resolution

no code implementations7 Jul 2021 Rao Muhammad Umer, Asad Munir, Christian Micheloni

The existing SR methods have limited performance due to a fixed degradation settings, i. e. usually a bicubic downscaling of low-resolution (LR) image.

Image Super-Resolution

Deep Iterative Residual Convolutional Network for Single Image Super-Resolution

1 code implementation7 Sep 2020 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 capabilities.

Image Super-Resolution

Deep Cyclic Generative Adversarial Residual Convolutional Networks for Real Image Super-Resolution

1 code implementation7 Sep 2020 Rao Muhammad Umer, Christian Micheloni

We consider a deep cyclic network structure to maintain the domain consistency between the LR and HR data distributions, which is inspired by the recent success of CycleGAN in the image-to-image translation applications.

Image Super-Resolution Image-to-Image Translation +1

Deep Generative Adversarial Residual Convolutional Networks for Real-World Super-Resolution

1 code implementation3 May 2020 Rao Muhammad Umer, Gian Luca Foresti, Christian Micheloni

Most current deep learning based single image super-resolution (SISR) methods focus on designing deeper / wider models to learn the non-linear mapping between low-resolution (LR) inputs and the high-resolution (HR) outputs from a large number of paired (LR/HR) training data.

Image Super-Resolution

Deep Super-Resolution Network for Single Image Super-Resolution with Realistic Degradations

no code implementations9 Sep 2019 Rao Muhammad Umer, Gian Luca Foresti, Christian Micheloni

Single Image Super-Resolution (SISR) aims to generate a high-resolution (HR) image of a given low-resolution (LR) image.

Image Super-Resolution

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