Timelapse: Rhone mouth in Geneva Lake - 2021

Publications associées (24)

Detecting submesoscale cold filaments in a basin-scale gyre in large, deep Lake Geneva (Switzerland/France)

David Andrew Barry, Ulrich Lemmin, Seyed Mahmood Hamze Ziabari, Amir Mehdi Razmi

Submesoscale filaments are a well-documented feature of oceanic flow fields. Based on the analysis of high-resolution 3D numerical simulations, field observations and remote sensing imagery, this study, carried out in Lake Geneva, Western Europe's largest ...

2022

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Detecting submesoscale cold filaments in a basin-scale gyre in large, deep Lake Geneva (Switzerland/France)

David Andrew Barry, Ulrich Lemmin, Seyed Mahmood Hamze Ziabari, Amir Mehdi Razmi

2022

MultiMAE: Multi-modal Multi-task Masked Autoencoders

Amir Roshan Zamir, Roman Christian Bachmann, Andrei Atanov, David Mizrahi

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 ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

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

Silvestro Micera, Daniela De Luca

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 ...

IEEE2022

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

Mathieu Salzmann, Vincent Lepetit, Yinlin Hu, Van Nguyen Nguyen, Yang Xiao

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 ...

IEEE COMPUTER SOC2022

Learning to Simulate Realistic LiDARs

Pascal Fua, Benoît Alain René Guillard

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 ...

2022

Multi-View Shape Estimation of Transparent Containers

Pascal Frossard, Andrea Cavallaro, Apostolos Modas

The 3D localisation of an object and the estimation of its properties, such as shape and dimensions, are challenging under varying degrees of transparency and lighting conditions. In this paper, we propose a method for jointly localising container-like obj ...

IEEE2020

Tracking Lagrangian transport in Lake Geneva: A 3D numerical modeling investigation

David Andrew Barry, Ulrich Lemmin, Andrea Cimatoribus

Lake Geneva, the largest freshwater lake in Western Europe, is subject to important environmental pressures from its densely populated shores and watershed. To maintain and improve water quality in this lake, as well as in other enclosed or semi‐enclosed b ...

American Society of Limnology and Oceanography2019

Application of an Ensemble Kalman filter to a semi-distributed hydrological flood forecasting system in alpine catchments

Giovanni De Cesare, Javier García Hernández, Alain Tommy Foehn, Anne Schwob

One of the key success factor for hydrological forecasts is the establishment of initial conditions that represent well the conditions of the simulated basin at the beginning of the forecast. Real-time Data Assimilation (DA) has been shown to allow improvi ...

2019

Wide Gamut Spectral Upsampling with Fluorescence

Wenzel Alban Jakob

Physically based spectral rendering has become increasingly important in recent years. However, asset textures in such systems are usually still drawn or acquired as RGB tristimulus values. While a number of RGB to spectrum upsampling techniques are availa ...

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

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Application of an Ensemble Kalman filter to a semi-distributed hydrological flood forecasting system in alpine catchments

Giovanni De Cesare, Javier García Hernández, Alain Tommy Foehn, Anne Schwob

2019

MultiMAE: Multi-modal Multi-task Masked Autoencoders

Amir Roshan Zamir, Roman Christian Bachmann, Andrei Atanov, David Mizrahi

SPRINGER INTERNATIONAL PUBLISHING AG2022