CORDONNIER , Guillaume

Convolutional neural networks (CNN) trained from high-order ice-flow model realisations have proven to be outstanding emulators in terms of fidelity and computational performance. However, the dependence on an ensemble of realisations of an instructor model renders this strategy difficult to generalise to a variety of ice-flow regimes found in...

Convolutional neural networks (CNN) trained from high-order ice-flow model realisations have proven to be outstanding emulators in terms of fidelity and computational performance. However, the dependence on an ensemble of realisations of an instructor model renders this strategy difficult to generalise to a variety of ice-flow regimes found in...

We present a novel approach to simulate large-scale lava flow in real-time. We use a depth-averaged model from numerical vulcanology to simplify the problem to 2.5D using a single layer of particle with thickness. Yet, lava flow simulation is challenging due to its strong viscosity which introduces computational instabilities. We solve the...

This paper introduces the Instructed Glacier Model (IGM) – a model that simulates ice dynamics, mass balance and its coupling to predict the evolution of glaciers, icefields or ice sheets. The novelty of IGM is that it models the ice flow by a Convolutional Neural Network, which is trained from data generated with hybrid SIA + SSA or Stokes ice...

Fluid control often uses optimization of control forces that are added to a simulation at each time step, such that the final animation matches a single or multiple target density keyframes provided by an artist. The optimization problem is strongly under-constrained with a high-dimensional parameter space, and finding optimal solutions is...

Solving linear system of equations stemming from Laplacian operators is at the heart of a wide range of applications. Due to the sparsity of the linear systems, iterative solvers such as Conjugate Gradient and Multigrid are usually employed when the solution has a large number of degrees of freedom. These iterative solvers can be seen as sparse...

The design of car shapes requires a delicate balance between aesthetic and performance. While fluid simulation provides themeans to evaluate the aerodynamic performance of a given shape, its computational cost hinders its usage during the early explorative phases of design, when aesthetic is decided upon. We present an interactive system to...

Terrain analysis plays an important role in computer graphics, hydrology and geomorphology. In particular, analyzing the path of material flow over a terrain with consideration of local depressions is a precursor to many further tasks in erosion, river formation, and plant ecosystem simulation. For example, fluvial erosion simulation used in...

Recent advances in Neural Radiance Fields enable the capture of scenes with motion. However, editing the motion is hard; no existing method allows editing beyond the space of motion existing in the original video, nor editing based on physics. We present the first approach that allows physically-based editing of motion in a scene captured with...

While the past of terrain cannot be known precisely because an effect can result from many different causes, exploring these possible pasts opens the way to numerous applications ranging from movies and games to paleogeography. We introduce unerosion, an attempt to recover plausible past topographies from an input terrain represented as a...

We introduce the first solution for simulating the formation and evolution of glaciers, together with their attendant erosive effects, for periods covering the combination of glacial and inter-glacial cycles. Our efficient solution includes both a fast yet accurate deep learning-based estimation of highorder ice flows and a new, multi-scale...

We propose an interactive animation method for the ejection of gas and ashes mixtures in volcano eruption. Our novel, layered solution combines a coarse-grain, physically-based simulation of the ejection dynamics with a consistent, procedural animation of multi-resolution details. We show that this layered model can be used to capture the two...

Creative processes of artists often start with hand-drawn sketches illustrating an object. Pre-visualizing these keyframes is especially challenging when applied to volumetric materials such as smoke. The authored 3D density volumes must capture realistic flow details and turbulent structures, which is highly non-trivial and remains a manual...

We present a novel method for authoring landscapes with flora and fauna while considering their mutual interactions. Our algorithm outputs a steadystate ecosystem in the form of density maps for each species, their daily circuits, and a modified terrain with eroded trails from a terrain, climatic conditions, and species with related biological...

Le programme de recherche ANR SCHOPPER, conçoit une nouvelle approche d'évaluation et de validation d'hypothèses de recherche sur les comportements des populations préhistoriques par l'utilisation de la réalité virtuelle (VR) et de l'intelligence artificielle (IA). Ce programme s'appuie sur le site paléolithique de la Caune de l'Arago, dans le...

Le programme de recherche ANR Schopper conçoit une nouvelle approche d'évaluation et de validation d'hypothèses de recherche sur les comportements des populations préhistoriques, par l'utilisation de la réalité virtuelle et de l'intelligence artificielle. Ce programme s'appuie sur le site paléolithique de la Caune de l'Arago (Tautavel,...