Publications associées à Autodesk 3ds Max

3DHumanGAN: 3D-Aware Human Image Generation with 3D Pose Mapping

We present 3DHumanGAN, a 3D-aware generative adversarial network that synthesizes photo-like images of fullbody humans with consistent appearances under different view-angles and body-poses. To tackle the representational and computational challenges in sy ...

Ieee Computer Soc2023

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

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

Katrin Beyer, Radhakrishna Achanta, 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

Robust Isometric Non-Rigid Structure-From-Motion

Shaifali Parashar

Non-Rigid Structure-from-Motion (NRSfM) reconstructs a deformable 3D object from keypoint correspondences established between monocular 2D images. Current NRSfM methods lack statistical robustness, which is the ability to cope with correspondence errors. T ...

IEEE COMPUTER SOC2022

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

Fast 3D Modeling of Prosthetic Robotic Hands Based on a Multi-Layer Deformable Design

Daniel Thalmann

Current research of designing prosthetic robotic hands mainly focuses on improving their functionality by devising new mechanical structures and actuation systems. Most of existing work relies on a single structure/system (e.g., bone-only or tissue-only) a ...

WHIOCE PUBLISHING PTE LTD, SINGAPORE2022

Sketch2Mesh: Reconstructing and Editing 3D Shapes from Sketches

Pascal Fua, Benoît Alain René Guillard, Edoardo Remelli, Pierre Mathieu Yvernay

Reconstructing 3D shape from 2D sketches has long been an open problem because the sketches only provide very sparse and ambiguous information. In this paper, we use an encoder/decoder architecture for the sketch to mesh translation. When integrated into a ...

IEEE2021

Neural Parts: Learning Expressive 3D Shape Abstractions with Invertible Neural Networks

Angelos Katharopoulos, Andreas Geiger, Despoina Paschalidou

Impressive progress in 3D shape extraction led to representations that can capture object geometries with high fidelity. In parallel, primitive-based methods seek to represent objects as semantically consistent part arrangements. However, due to the simpli ...

IEEE COMPUTER SOC2021

Slope-Space Integrals for Specular Next Event Estimation

Wenzel Alban Jakob, Tizian Lucien Zeltner, Guillaume Rémi Bruno Loubet

Monte Carlo light transport simulations often lack robustness in scenes containing specular or near-specular materials. Widely used uni- and bidirectional sampling strategies tend to find light paths involving such materials with insufficient probability, ...

ASSOC COMPUTING MACHINERY2020

A Dexterous Soft Robotic Hand for Delicate In-Hand Manipulation

In this letter, we show that soft robotic hands provide a robust means of performing basic primitives of in-hand manipulation in the presence of uncertainty. We first discuss the design of a prototype hand with dexterous soft fingers capable of moving obje ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Voxel2Mesh: 3D Mesh Model Generation from Volumetric Data

Pascal Fua, Graham Knott, Edoardo Remelli, Pamuditha Udaranga Wickramasinghe

CNN-based volumetric methods that label individual voxels now dominate the field of biomedical segmentation. However, 3D surface representations are often required for proper analysis. They can be obtained by post-processing the labeled volumes which typic ...

2020

The OFFBEAT multi-dimensional fuel behavior solver

Andreas Pautz, Carlo Fiorina, Alessandro Scolaro

The OpenFOAM Fuel BEhavior Analysis Tool, or OFFBEAT, is a multi-dimensional fuel performance code under collaborative development at the Laboratory for Reactor Physics and Systems Behaviour (LRS) of the EPFL and at the PSI. The code can be used both for s ...

ELSEVIER SCIENCE SA2020

UCLID-Net: Single View Reconstruction in Object Space

Pascal Fua, Benoît Alain René Guillard, Edoardo Remelli

Most state-of-the-art deep geometric learning single-view reconstruction approaches rely on encoder-decoder architectures that output either shape parametrizations or implicit representations. However, these representations rarely preserve the Euclidean st ...

2020

GarNet: A Two-Stream Network for Fast and Accurate 3D Cloth Draping

Pascal Fua, Mathieu Salzmann, Victor Constantin, Erhan Gündogdu

While Physics-Based Simulation (PBS) can accurately drape a 3D garment on a 3D body, it remains too costly for real-time applications, such as virtual try-on. By contrast, inference in a deep network, requiring a single forward pass, is much faster. Taking ...

IEEE2019

Generating High Fidelity Surface Meshes of Neocortical Neurons using Skin Modifiers

Felix Schürmann, Marwan Muhammad Ahmed Abdellah, Juan Bautista Hernando Vieites, Cyrille Pierre Henri Favreau, Samuel Lieven D. Lapere

We present the results of exploring the capabilities of skinning modifiers to generate high fidelity polygonal surface meshes of neurons from their morphological skeletons that are segmented from optical microscopy slides. Our algorithm is implemented in B ...

2019

Normal-Based Interpolating Subdivision For The Geometric Representation Of Deformable Models

Michaël Unser, Anaïs Laure Marie-Thérèse Badoual

We review the normal-based interpolating subdivision scheme proposed in [1]. We show that it allows the user to exactly represent circles/spheres whenever suitable initial data are provided, and we also prove that it enjoys the property of similarity invar ...

IEEE2019

Adaptive Isogeometric Methods With Hierarchical Splines: An Overview

Annalisa Buffa, Rafael Vazquez Hernandez

We consider an adaptive isogeometric method (AIGM) based on (truncated) hierarchical B-splines and present the study of its numerical properties. By following [10, 12, 11], optimal convergence rates of the AIGM can be proved when suitable approximation cla ...

2019

Three-Dimensional Model and Evaluation of an Insulin Injection Pen for Precise Dose Capacitive Measurement

Catherine Dehollain, Maria-Alexandra Paun, Jean-Baptiste Robert Orhan

A fully parameterized three-dimensional model with specific dimensions has been developed in ANSYS for an insulin injection pen used by diabetic persons. The insulin injection pen has a smart pen cap which hosts four electrodes used for the smart pen cap e ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2019

DeepFly3D, a deep learning-based approach for 3D limb and appendage tracking in tethered, adult Drosophila

Pascal Fua, Pavan P Ramdya, Helge Jochen Rhodin, Semih Günel, Daniel Eduardo Morales Garza, João Henrique Campagnolo

Studying how neural circuits orchestrate limbed behaviors requires the precise measurement of the positions of each appendage in 3-dimensional (3D) space. Deep neural networks can estimate 2-dimensional (2D) pose in freely behaving and tethered animals. Ho ...

2019