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Related publications (34)

Linear-Covariance Loss for End-to-End Learning of 6D Pose Estimation

Most modern image-based 6D object pose estimation methods learn to predict 2D-3D correspondences, from which the pose can be obtained using a PnP solver. Because of the non-differentiable nature of common PnP solvers, these methods are supervised via the i ...

Ieee Computer Soc2023

On the Performance of Subjective Visual Quality Assessment Protocols for Nearly Visually Lossless Image Compression

Touradj Ebrahimi, Michela Testolina

The past decades have witnessed rapid growth in imaging as a major form of communication between individuals. Due to recent advances in capture, storage, delivery and display technologies, consumers demand improved perceptual quality while requiring reduce ...

2023

T-RECS: a Transformer-based Recommender Generating Textual Explanations and Integrating Unsupervised Language-based Critiquing

Boi Faltings, Claudiu-Cristian Musat, Diego Matteo Antognini

Supporting recommendations with personalized and relevant explanations increases trust and perceived quality, and helps users make better decisions. Prior work attempted to generate a synthetic review or review segment as an explanation, but they were not ...

2022

Design and Validation of a Compact Embedded Photometric Device for Real-time Daylighting Computing in Office Buildings

Jean-Louis Scartezzini, Jérôme Henri Kämpf, Yujie Wu

Studies have shown that the exposure to daylight can have substantial visual/non-visual benefits for building occupants. To optimise daylighting provision while maintaining a comfortable visual environment, daylighting control systems have been investigate ...

2019

Deep Semantic Segmentation Using Nir As Extra Physical Information

Sabine Süsstrunk, Siavash Arjomand Bigdeli

Deep neural networks for semantic segmentation are most often trained with RGB color images, which encode the radiation visible to the human eyes. In this paper, we study if additional physical scene information, specifically Near-Infrared (NIR) images, im ...

IEEE2019

A Low-Dimensional Function Space for Efficient Spectral Upsampling

Wenzel Alban Jakob

We present a versatile technique to convert textures with tristimulus colors into the spectral domain, allowing such content to be used in modern rendering systems. Our method is based on the observation that suitable reflectance spectra can be represented ...

WILEY2019

Compression and visual quality assessment for light field contents

Irene Viola

Since its invention in the 19th century, photography has allowed to create durable images of the world around us by capturing the intensity of light that flows through a scene, first analogically by using light-sensitive material, and then, with the advent ...

EPFL2019

Evaluation of ICtCp color space and an Adaptive Reshaper for HDR and WCG

Touradj Ebrahimi, Martin Rerabek, Anne-Flore Nicole Marie Perrin

New emerging technologies in the field of multimedia, such as high dynamic range and wide color gamut, challenge the performance of existing image and video data processing algorithms, especially in terms of visual data compression and its faithful represe ...

2018

Evaluation of JPEG XT for high dynamic range cameras

Touradj Ebrahimi, Philippe Hanhart

Modern cameras can be used to capture high dynamic range (HDR) images by taking multiple low dynamic range (LDR) pictures at different exposure settings. However, DSLR cameras often store the multiple exposure pictures, which increases storage requirements ...

Elsevier Science Bv2017

An Algorithm Architecture Co-Design for CMOS Compressive High Dynamic Range Imaging

Pierre Vandergheynst, William Guicquéro, Antoine Dupret

Standard image sensors feature dynamic range about 60 to 70 dB while the light flux of natural scenes may be over 120 dB. Most imagers dedicated to address such dynamic ranges, need specific, and large pixels. However, canonical imagers can be used for hig ...

Ieee-Inst Electrical Electronics Engineers Inc2016

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