NTIRE 2018 Challenge on Spectral Reconstruction from RGB Images

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Tomographic imaging of time-evolving samples is a challenging yet important task for various research fields. At the nanoscale, current approaches face limitations of measurement speed or resolution due to lengthy acquisitions. We developed a dynamic nanot ...

We measure the metallicities of 374 red giant branch (RGB) stars in the isolated, quenched dwarf galaxy Tucana using Hubble Space Telescope (HST) narrow-band (F395N) Calcium H & K (CaHK) imaging. Our sample is a factor of similar to 7 similar to 7 larger t ...

We introduce a new family of single-photon avalanche diodes (SPADs) with enhanced depletion regions in a 55-nm Bipolar-CMOS-DMOS (BCD) technology. We demonstrate how to systematically engineer doping profiles in the main junction and in deep p-well layers ...

The dataset is a collection of RGB and thermal images of the Rhone mouth in Geneva Lake, taken every minute in 2022. ...

The dataset is a collection of RGB and thermal images of the Rhone mouth in Geneva Lake, taken every minute from January to August 2023. ...

The dataset is a collection of RGB and thermal images of the Rhone mouth in Geneva Lake, taken every minute in 2021. ...

The dataset is a collection of RGB and thermal images of the Rhone mouth in Geneva Lake, taken every minute in 2019. ...

The dataset is a collection of RGB and thermal images of the Rhone mouth in Geneva Lake, taken every minute in 2017. ...

The dataset is a collection of RGB and thermal images of the Rhone mouth in Geneva Lake, taken every minute in 2019. ...

Tomographic X-ray imaging techniques offer novel opportunities for studying membranes and membrane processes in 3D on a spatial resolution not seen before. Traditional 2D imaging techniques used to characterise membranes have limitations that can be overco ...

The transition towards a human-centered indoor climate is beneficial from occupants’ thermal comfort and from an energy reduction perspective. However, achieving this goal requires the knowledge of the thermal state of individuals at the level of body part ...

Controlling and shaping radiation beams is fundamental for a better understanding of radiation-matter interaction and advancing experimental techniques for material characterization at high spatial resolution. In particular, the current trend in the miniat ...

Recent advances in image compression have made it both possible and desirable for image quality to approach the visually lossless range. However, the most commonly used subjective visual quality assessment protocols, e.g. those reported in ITU-T Rec. BT.50 ...

Sensing and projecting an individual’s human thermal comfort in buildings is a complex but crucial task for transitioning toward human-centered indoor climate control. Non-intrusive collection of physiological and personal information from the human body, ...

We propose a pre-training strategy called Multi-modal Multi-task Masked Autoencoders (MultiMAE). It differs from standard Masked Autoencoding in two key aspects: I) it can optionally accept additional modalities of information in the input besides the RGB ...

We present a method that can recognize new objects and estimate their 3D pose in RGB images even under partial occlusions. Our method requires neither a training phase on these objects nor real images depicting them, only their CAD models. It relies on a s ...

The COVID-19 pandemic outbreak is causing a dramatic worsening in the already complicated living conditions of blind and visually impaired individuals. Social distancing is the most effective strategy to limit virus spread, but is extremely difficult for b ...

Simulating realistic sensors is a challenging part in data generation for autonomous systems, often involving carefully handcrafted sensor design, scene properties, and physics modeling. To alleviate this, we introduce a pipeline for data-driven simulation ...

Due to the increasing number of pictures captured and stored every day by and on digital devices, lossy image compression has become inevitable to limit the needed storage requirement. As a consequence, these compression methods might introduce some visual ...

State-of-the-art 2D image compression schemes rely on the power of convolutional neural networks (CNNs). Although CNNs offer promising perspectives for 2D image compression, extending such models to omnidirectional images is not straightforward. First, omn ...

NTIRE 2018 Challenge on Spectral Reconstruction from RGB Images

Chattez avec Graph Search

Dynamic sparse x-ray nanotomography reveals ionomer hydration mechanism in polymer electrolyte fuel-cell catalyst

Stellar Metallicities and Gradients in the Isolated, Quenched Low-mass Galaxy Tucana

Doping Engineering for PDP Optimization in SPADs Implemented in 55-nm BCD Process

Timelapse: Rhone mouth in Geneva Lake - 2022

Timelapse: Rhone mouth in Geneva Lake - 2023

Timelapse: Rhone mouth in Geneva Lake - 2021

Timelapse: Geneva Lake, in front of Chexbres - 2019

Timelapse: Rhone mouth in Geneva Lake - 2017

Timelapse: Rhone mouth in Geneva Lake - 2019

Towards multiscale X-ray tomographic imaging in membrane science - A perspective

Toward contactless human thermal monitoring: A framework for Machine Learning-based human thermo-physiology modeling augmented with computer vision

Quantum engineering and detection of advanced radiation beams

On the assessment of high-quality images: advances on the JPEG AIC-3 activity

Non-intrusive physiological parameters sensing for personalized human thermal comfort prediction

MultiMAE: Multi-modal Multi-task Masked Autoencoders

Templates for 3D Object Pose Estimation Revisited: Generalization to New Objects and Robustness to Occlusions

Deploying an Instance Segmentation Algorithm to Implement Social Distancing for Prosthetic Vision

Learning to Simulate Realistic LiDARs

Towards JPEG AIC part 3: visual quality assessment of high to visually lossless image coding

OSLO: On-the-Sphere Learning for Omnidirectional Images and Its Application to 360-Degree Image Compression