Geometry-aware Deep Network for Single-Image Novel View Synthesis

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The Supersingular Isogeny Diffie-Hellman (SIDH) protocol has been the main and most efficient isogeny-based encryption protocol, until a series of breakthroughs led to a polynomial-time key-recovery attack. While some countermeasures have been proposed, th ...

In recent years, new emerging immersive imaging modalities, e.g. light fields, have been receiving growing attention, becoming increasingly widespread over the years. Light fields are often captured through multi-camera arrays or plenoptic cameras, with th ...

Artificial Neural Networks (ANN) are habitually trained via the back-propagation (BP) algorithm. This approach has been extremely successful: Current models like GPT-3 have O(10 11 ) parameters, are trained on O(10 11 ) words and produce awe-inspiring resu ...

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The generation of 3D models depicting cities in the past holds great potential for documentation and educational purposes. However, it is often hindered by incomplete historical data and the specialized expertise required. To address these challenges, we p ...

Incidents where water networks are contaminated with microorganisms or pollutants can result in a large number of infected or ill persons, and it is therefore important to quickly detect, localize and estimate the spread and source of the contamination. In ...

LES and wind tunnel studies have shown significant benefit when allowing turbines (T) in a wind farm to adopt different heights. This work presents two new genetic algorithms (GA) that perform wind farm layout optimization (WFLO) involving continuous and t ...

Headwater streams often experience intermittent flow. Consequently, the flowing drainage network expands and contracts and the flowing drainage density (DD) varies over time. Monitoring the DD dynamics is essential to understand the processes controlling i ...

We show that isogeometric Galerkin discretizations of eigenvalue problems related to the Laplace operator subject to any standard type of homogeneous boundary conditions have no outliers in certain optimal spline subspaces. Roughly speaking, these optimal ...

We are used to defining network neutrality as absence of traffic differentiation, like policing or shaping. These mechanisms, however, are often not what determines end-users’ quality of experience (QoE). Most content today is accessed through edge caches, ...

We show the Jordan property for regional fundamental groups of klt singularities of fixed dimension. Furthermore, we prove the existence of effective simultaneous index 1 covers for n-dimensional klt singularities. We give an application to the study of lo ...

We propose nonparametric estimators for the second-order central moments of possibly anisotropic spherical random fields, within a functional data analysis context. We consider a measurement framework where each random field among an identically distribute ...

Geometry-aware Deep Network for Single-Image Novel View Synthesis

Chattez avec Graph Search

New SIDH Countermeasures for a More Efficient Key Exchange

Towards learning-based denoising of light fields

Artificial Neural Network Training on an Optical Processor via Direct Feedback Alignment

3D reconstruction of curvilinear one-dimensional objects viewed in transmission electron microscopy

Machine-Learning-Enhanced Procedural Modeling for 4D Historical Cities Reconstruction

Estimating pollution spread in water networks as a Schrödinger bridge problem with partial information

Wind farm layout and unconstrained hub height optimization using genetic algorithms applied to different power densities

Short-term dynamics of drainage density based on a combination of channel flow state surveys and water level measurements

Application of optimal spline subspaces for the removal of spurious outliers in isogeometric discretizations

Caching and Neutrality

The Jordan property for local fundamental groups

Functional estimation of anisotropic covariance and autocovariance operators on the sphere