Publications related to Polygonal modeling

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

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

An a posteriori error estimator for isogeometric analysis on trimmed geometries

Annalisa Buffa, Rafael Vazquez Hernandez, Ondine Gabrielle Chanon

Trimming consists of cutting away parts of a geometric domain, without reconstructing a global parametrization (meshing). It is a widely used operation in computer-aided design, which generates meshes that are unfitted with the described physical object. T ...

2022

Pedestrian 3D Bounding Box Prediction

Alexandre Massoud Alahi, Saeed Saadatnejad, Yi Zhou Ju

Safety is still the main issue of autonomous driving, and in order to be globally deployed, they need to predict pedestrians' motions sufficiently in advance. While there is a lot of research on coarse-grained (human center prediction) and fine-grained pre ...

2022

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

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

A Non-Exponential Transmittance Model for Volumetric Scene Representations

Wenzel Alban Jakob, Delio Aleardo Vicini

We introduce a novel transmittance model to improve the volumetric representation of 3D scenes. The model can represent opaque surfaces in the volumetric light transport framework. Volumetric representations are useful for complex scenes, and become increa ...

ASSOC COMPUTING MACHINERY2021

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

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Polygonal modeling

Robust Isometric Non-Rigid Structure-From-Motion

Differentiable Signed Distance Function Rendering

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

An a posteriori error estimator for isogeometric analysis on trimmed geometries

Pedestrian 3D Bounding Box Prediction

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

Sketch2Mesh: Reconstructing and Editing 3D Shapes from Sketches

A Non-Exponential Transmittance Model for Volumetric Scene Representations

Tessellation and lmprovement of Simplicial Meshes using Neural Networks

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

Graph Chatbot

Chat with Graph Search

An a posteriori error estimator for isogeometric analysis on trimmed geometries

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

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

Robust Isometric Non-Rigid Structure-From-Motion

Differentiable Signed Distance Function Rendering

Pedestrian 3D Bounding Box Prediction

Sketch2Mesh: Reconstructing and Editing 3D Shapes from Sketches

A Non-Exponential Transmittance Model for Volumetric Scene Representations

Tessellation and lmprovement of Simplicial Meshes using Neural Networks

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