Publications by Fayez Lahoud | EPFL Graph Search

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Despite the advances in single-image super resolution using deep convolutional networks, the main problem remains unsolved: recovering fine texture details. Recent works in super resolution aim at modifying the training of neural networks to enable the rec ...

Recent advances have shown the great power of deep convolutional neural networks (CNN) to learn the relationship between low and high-resolution image patches. However, these methods only take a single-scale image as input and require large amount of data ...

Clinical applications, such as image-guided surgery and noninvasive diagnosis, rely heavily on multi-modal images. Medical image fusion plays a central role by integrating information from multiple sources into a single, more understandable output. We prop ...

Developing an augmented reality (AR) system involves multiple algorithms such as image fusion, camera synchronization and calibration, and brightness control, each of them having diverse variants. This abundance of features, while beneficial in nature, is ...

This paper reviews the first challenge on spectral image reconstruction from RGB images, i.e., the recovery of whole-scene hyperspectral (HS) information from a 3- channel RGB image. The challenge was divided into 2 tracks: the “Clean” track sought HS reco ...

Developing an augmented reality (AR) system involves a multitude of interconnected algorithms such as image fusion, camera synchronization and calibration, and brightness control, each having diverse parameters. This abundance of features, while beneficial ...

Keyword-based image color re-rendering is a convenient way to enhance the color of images. Most methods only focus on the color characteristics of the image while ignoring the semantic meaning of different regions. We propose to incorporate semantic inform ...

Fayez Lahoud

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A comparative study on wavelets and residuals in deep super resolution

Multi-Modal Spectral Image Super-Resolution

Zero-Learning Fast Medical Image Fusion

AR in VR: Simulating Infrared Augmented Vision

Zero-Learning Fast Medical Image Fusion

NTIRE 2018 Challenge on Spectral Reconstruction from RGB Images

AR in VR: Simulating augmented reality glass for image fusion

Keyword-based Image Color Re-rendering with Semantic Segmentation