Publications by Edoardo Remelli

DeepMesh: Differentiable Iso-Surface Extraction

Pascal Fua, Timur Bagautdinov, Pierre Bruno Baqué, Edoardo Remelli, Benoît Alain René Guillard, Pierre Mathieu Yvernay

2024

DIG: Draping Implicit Garment over the Human Body

Pascal Fua, Edoardo Remelli, Benoît Alain René Guillard, Ren Li

Existing data-driven methods for draping garments over human bodies, despite being effective, cannot handle garments of arbitrary topology and are typically not end-to-end differentiable. To address these limitations, we propose an end-to-end differentiabl ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

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

Sketch2Mesh: Reconstructing and Editing 3D Shapes from Sketches

Pascal Fua, Edoardo Remelli, Benoît Alain René Guillard, 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

UCLID-Net: Single View Reconstruction in Object Space

Pascal Fua, Edoardo Remelli, Benoît Alain René Guillard

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

MeshSDF: Differentiable Iso-Surface Extraction

Pascal Fua, Timur Bagautdinov, Pierre Bruno Baqué, Edoardo Remelli, Benoît Alain René Guillard, Artem Lukoianov

2020

Voxel2Mesh: 3D Mesh Model Generation from Volumetric Data

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

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

Geodesic Convolutional Shape Optimization

Pascal Fua, François Fleuret, Pierre Bruno Baqué, Edoardo Remelli

Aerodynamic shape optimization has many industrial applications. Existing methods, however, are so computationally demanding that typical engineering practices are to either simply try a limited number of hand-designed shapes or restrict oneself to shapes ...

2018

Online Generative Model Personalization for Hand Tracking

Mark Pauly, Anastasia Tkach, Andrea Tagliasacchi, Edoardo Remelli

We present a new algorithm for real-time hand tracking on commodity depth-sensing devices. Our method does not require a user-specific calibration session, but rather learns the geometry as the user performs live in front of the camera, thus enabling seaml ...

Assoc Computing Machinery2017