Publications related to Geometry processing

Sketch2Mesh: Reconstructing and Editing 3D Shapes from Sketches

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

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

Fast end-to-end learning on protein surfaces

Bruno Emanuel Ferreira De Sousa Correia, Freyr Sverrisson

Proteins' biological functions are defined by the geometric and chemical structure of their 3D molecular surfaces. Recent works have shown that geometric deep learning can be used on mesh-based representations of proteins to identify potential functional s ...

IEEE COMPUTER SOC2021

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

Learning Lipschitz-Controlled Activation Functions in Neural Networks for Plug-and-Play Image Reconstruction Methods

Michaël Unser, Dimitris Perdios, Pakshal Narendra Bohra, Alexis Marie Frederic Goujon, Sébastien Alexandre Emery

Ill-posed linear inverse problems are frequently encountered in image reconstruction tasks. Image reconstruction methods that combine the Plug-and-Play (PnP) priors framework with convolutional neural network (CNN) based denoisers have shown impressive per ...

2021

How to teach neural networks to mesh: Application on 2-D simplicial contours

François Avellan, Pascal Clausen, Alexis Papagiannopoulos

A machine learning meshing scheme for the generation of 2-D simplicial meshes is proposed based on the predictions of neural networks. The data extracted from meshed contours are utilized to train neural networks which are used to approximate the number of ...

2021

2d-3d sculpture paintings

Sabine Süsstrunk, Roger Hersch, Mahmut Sami Arpa

We disclose a method for synthesizing by computer an artwork where 2D and 3D contents are integrated within a same composition. Such an artwork creates plausible effects for the viewers by showing a different relationship between 2D and 3D at each viewing ...

2020

Two-Dimensional RBF-ENO Method on Unstructured Grids

Jan Sickmann Hesthaven, Fabian Mönkeberg

Essentially non-oscillatory (ENO) and weighted ENO (WENO) methods on equidistant Cartesian grids are widely used to solve partial differential equations with discontinuous solutions. However, stable ENO/WENO methods on unstructured grids are less well stud ...

SPRINGER/PLENUM PUBLISHERS2020

Assessing the Efficacy of a GPU-Based MW-FDTD Method for Calculating Lightning Electromagnetic Fields Over Large-Scale Terrains

Marcos Rubinstein, Mohammad Azadifar, Farhad Rachidi-Haeri, Hamidreza Karami

This article presents for the first time an OpenACC (Open accelerators)-aided Graphics Processing Unit (GPU)-based approach adopting a 3D moving window finite difference time domain (MW-FDTD) method for calculating lightning electromagnetic fields over lar ...

2020

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Geometry processing

Sketch2Mesh: Reconstructing and Editing 3D Shapes from Sketches

Remarks on Poincare and interpolation estimates for Truncated Hierarchical B-splines

Fast end-to-end learning on protein surfaces

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

Learning Lipschitz-Controlled Activation Functions in Neural Networks for Plug-and-Play Image Reconstruction Methods

How to teach neural networks to mesh: Application on 2-D simplicial contours

2d-3d sculpture paintings

High-order essentially nonoscillatory methods based on radial basis functions

Two-Dimensional RBF-ENO Method on Unstructured Grids

Assessing the Efficacy of a GPU-Based MW-FDTD Method for Calculating Lightning Electromagnetic Fields Over Large-Scale Terrains

Graph Chatbot

Chat with Graph Search

High-order essentially nonoscillatory methods based on radial basis functions

Two-Dimensional RBF-ENO Method on Unstructured Grids

Remarks on Poincare and interpolation estimates for Truncated Hierarchical B-splines

Sketch2Mesh: Reconstructing and Editing 3D Shapes from Sketches

Fast end-to-end learning on protein surfaces

How to teach neural networks to mesh: Application on 2-D simplicial contours

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

Learning Lipschitz-Controlled Activation Functions in Neural Networks for Plug-and-Play Image Reconstruction Methods

2d-3d sculpture paintings

Assessing the Efficacy of a GPU-Based MW-FDTD Method for Calculating Lightning Electromagnetic Fields Over Large-Scale Terrains