Publications associées à Geometry processing

Semantic Shape Editing with Parametric Implicit Templates

We propose a semantic shape editing method to edit 3D triangle meshes using parametric implicit surface templates, benefiting from the many advantages offered by analytical implicit representations, such as infinite resolution and boolean or blending opera ...

ACM Association for Computing Machinery2024

Automatic Parameterization for Aerodynamic Shape Optimization via Deep Geometric Learning

Pascal Fua, Zhen Wei

We propose two deep learning models that fully automate shape parameterization for aerodynamic shape optimization. Both models are optimized to parameterize via deep geometric learning to embed human prior knowledge into learned geometric patterns, elimina ...

2023

Analysis-aware defeaturing of complex geometries with Neumann features

Pablo Antolin Sanchez, Ondine Gabrielle Chanon

Local modifications of a computational domain are often performed in order to simplify the meshing process and to reduce computational costs and memory requirements. However, removing geometrical features of a domain often introduces a non-negligible error ...

Wiley2023

Latent Representation of Computational Fluid Dynamics Meshes and Application to Airfoil Aerodynamics

Pascal Fua, Benoît Alain René Guillard, Zhen Wei

Mesh manipulation is central to computational fluid dynamics. However, creating appropriate computational meshes often involves substantial manual intervention that has to be repeated each time the target shape changes. To address this problem, we propose ...

AMER INST AERONAUTICS ASTRONAUTICS2023

A method and system for enforcing smoothness constraints on surface meshes from a graph convolutional neural network

Pascal Fua, Pamuditha Udaranga Wickramasinghe

A method for enforcing smoothness constraints on surface meshes produced by a Graph Convolutional Neural Network (GCNN) including the steps of reading image data from a memory, the image data including two-dimensional image data representing a three-dimens ...

2023

Deep Learning for 3D Surface Modelling and Reconstruction

Benoît Alain René Guillard

In recent years, there has been a significant revolution in the field of deep learning, which has demonstrated its effectiveness in automatically capturing intricate patterns from large datasets. However, the majority of these successes in Computer Vision ...

EPFL2023

OrthoPlanes: A Novel Representation for Better 3D-Awareness of GANs

Zhuoqian Yang, Siyuan Li

We present a new method for generating realistic and view-consistent images with fine geometry from 2D image collections. Our method proposes a hybrid explicitimplicit representation called OrthoPlanes, which encodes fine-grained 3D information in feature ...

Ieee Computer Soc2023

Differentiable Signed Distance Function Rendering

Wenzel Alban Jakob, Delio Aleardo Vicini, Sébastien Nicolas Speierer

Physically-based differentiable rendering has recently emerged as an attractive new technique for solving inverse problems that recover complete 3D scene representations from images. The inversion of shape parameters is of particular interest but also pose ...

ASSOC COMPUTING MACHINERY2022

Reduced order modelling of nonaffine problems on parameterized NURBS multipatch geometries

Annalisa Buffa, Pablo Antolin Sanchez, Margarita Chasapi

This contribution explores the combined capabilities of reduced basis methods and IsoGeometric Analysis (IGA) in the context of parameterized partial differential equations. The introduction of IGA enables a unified simulation framework based on a single g ...

2022

Synthesis and Analysis of 3D shapes with Geometric Deep Learning in Computer-Aided Engineering

Edoardo Remelli

In this thesis, we advocate that Computer-Aided Engineering could benefit from a Geometric Deep Learning revolution, similarly to the way that Deep Learning revolutionized Computer Vision. To do so, we consider a variety of Computer-Aided Engineering pr ...

EPFL2022