Publications associées à 2d-3d sculpture paintings

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

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

Seyed Mohammad Mahdi Johari

Recent advancements in deep learning have revolutionized 3D computer vision, enabling the extraction of intricate 3D information from 2D images and video sequences. This thesis explores the application of deep learning in three crucial challenges of 3D com ...

EPFL2024

Aggregating Spatial and Photometric Context for Photometric Stereo

David Honzátko

Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

EPFL2024

3D diffractive optics for linear interconnects and nonlinear processing

Niyazi Ulas Dinç

The optical domain presents potential avenues for enhancing both computing and communication due to its inherent properties of bandwidth, parallelism, and energy efficiency. This research focuses on harnessing 3-Dimensional (3D) diffractive optics for nove ...

EPFL2024

An adaptive phase field approach to 3D internal crack growth in rocks

Tao Xu, Michael Heap, Alexandra Roma Larisa Kushnir

Modeling the 3D internal crack under compression entails complex fracture mechanics (mode I-II-III fracture), resulting in substantial computational costs and challenges in characterizing fracture morphology characterization for Phase Field Method (PFM) si ...

2024

Modular segmentation, spatial analysis and visualization of volume electron microscopy datasets

Martin Weigert

Volume electron microscopy is the method of choice for the in situ interrogation of cellular ultrastructure at the nanometer scale, and with the increase in large raw image datasets generated, improving computational strategies for image segmentation and s ...

Nature Portfolio2024

Multimaterial Volumetric Printing of Silica-Based Glasses

Christophe Moser, Damien Claude-Marie Loterie, Paul Delrot, Jorge Andres Madrid Wolff, Antoine Vincent Boniface, Roberto Arturo Emma

Silicate glasses have played a major role as structural and functional materials in human civilization since ancient Egypt. Despite their widespread use and importance in modern society, silica glasses with complex geometries are only fabricated in automat ...

Wiley2024

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

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

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

Automated post-earthquake damage assessment of stone masonry buildings integrating machine learning, computer vision, and physics-based modeling

Bryan German Pantoja Rosero

Current post-earthquake damage assessment methodologies are not only time-consuming but also subjective in nature and difficult to document. Recent advancements in artificial intelligence and technological devices make it possible to accomplish this task a ...

EPFL2023

ISP: Multi-Layered Garment Draping with Implicit Sewing Patterns

Pascal Fua, Benoît Alain René Guillard, Ren Li

Many approaches to draping individual garments on human body models are realistic, fast, and yield outputs that are differentiable with respect to the body shape on which they are draped. However, they are either unable to handle multi-layered clothing, wh ...

2023

Automated image-based generation of finite element models for masonry buildings

Radhakrishna Achanta, Katrin Beyer, Bryan German Pantoja Rosero

To predict the response of masonry buildings to various types of loads, engineers use finite element models, specifically solid-element and macro-element models. For predicting masonry responses to seismic events in particular, equivalent frame models-a su ...

SPRINGER2023

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

Gulnaz Ganeeva

To obtain a more complete understanding of material microstructure at the nanoscale and to gain profound insights into their properties, there is a growing need for more efficient and precise methods that can streamline the process of 3D imaging using a tr ...

EPFL2023

The physics of 3D printing with light

Christophe Moser

The goal of 3D printing is to realize complex 3D structures by locally adding material in small volume elements called voxels - in contrast to successively subtracting material by etching, milling or machining. This field started with optics-based proposal ...

Nature Portfolio2023

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

Differentiable Signed Distance Function Rendering

Sébastien Nicolas Speierer, Wenzel Alban Jakob, Delio Aleardo Vicini

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

Image-based geometric digital twinning for stone masonry elements

Katrin Beyer, Bryan German Pantoja Rosero, Savvas Saloustros

We present an image-based pipeline for generating geometrical digital twins (GDTs) of stone masonry elements with detail down to the stone level. For this purpose, we acquire RGB images of the individual stones and of the wall during the construction phase ...

2022

Bragg edge tomography characterization of additively manufactured 316L steel

Christian Leinenbach, Roland Logé, Nikola Kalentics, Efthymios Polatidis, Markus Strobl

In this work we perform a neutron Bragg edge tomography of stainless steel 316L additive manufacturing samples, one as built via standard laser powder bed fusion, and one using the novel three-dimensional (3D) laser shock peening technique. First, we consi ...

AMER PHYSICAL SOC2022

Sub-micrometer morphology of human atherosclerotic plaque revealed by synchrotron radiation-based mu CT-A comparison with histology

Anne Bonnin, Goran Lovric

Histology is a long standing and well-established gold standard for pathological characterizations. In recent years however, synchrotron radiation-based micro-computed tomography (SR mu CT) has become a tool for extending the imaging of two-dimensional thi ...

PUBLIC LIBRARY SCIENCE2022