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

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.

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 ...

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 ...

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 ...

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 ...

The generation of 3D models depicting cities in the past holds great potential for documentation and educational purposes. However, it is often hindered by incomplete historical data and the specialized expertise required. To address these challenges, we p ...

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 ...

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 ...

Representing and reconstructing 3D deformable shapes are two tightly linked problems that have long been studied within the computer vision field. Deformable shapes are truly ubiquitous in the real world, whether be it specific object classes such as human ...

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 ...

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 ...

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 ...

Neurons are characterized by thin and long interleaving arborizations in which creating accurate mesh models of their cellular membranes is challenging. While union operators are central for CAD/CAM modeling and computer graphics applications, their applic ...

Detailed micromodel simulations of stone masonry walls require as input a 3D mesh that represents a realistic arrangement of stones in the masonry wall. In this paper, we constructed the first 3D masonry microstructures to derive 2D and 3D finite or discre ...

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 ...

We present a pipeline for the automatic generation of digital twins of free-standing buildings for damage assessment. Our method takes multiple view images of the target building as input and processes them to produce a 3D model in levels of detail (LOD) f ...

This contribution explores the combined capabilities of reduced basis methods and IsoGeometric Analysis (IGA) in the context of parameterized partial differential equations. The introduction of IGA enables a unified simulation framework based on a single g ...

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 ...

We present a novel isogeometric method, namely the Immersed Boundary-Conformal Method (IBCM), that features a layer of discretization conformal to the boundary while employing a simple background mesh for the remaining domain. In this manner, we leverage t ...

The human face plays an essential role in social interactions as it brings information about someone's identity, state of mind, or mood. People are, by nature, very good at catching this non-spoken information. Therefore, scientists have been interested in ...

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 ...

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

Chat with Graph Search

Semantic Shape Editing with Parametric Implicit Templates

Aggregating Spatial and Photometric Context for Photometric Stereo

Deep Learning for 3D Surface Modelling and Reconstruction

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

Machine-Learning-Enhanced Procedural Modeling for 4D Historical Cities Reconstruction

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

Synthesis and Analysis of 3D shapes with Geometric Deep Learning in Computer-Aided Engineering

Learning to Represent and Reconstruct 3D Deformable Objects

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

Differentiable Signed Distance Function Rendering

Robust Isometric Non-Rigid Structure-From-Motion

Meshing of Spiny Neuronal Morphologies using Union Operators

A virtual microstructure generator for 3D stone masonry walls

Image-based geometric digital twinning for stone masonry elements

Digital twins for post-earthquake damage assessment of free-standing buildings including damage information

Reduced order modelling of nonaffine problems on parameterized NURBS multipatch geometries

Sketch2Mesh: Reconstructing and Editing 3D Shapes from Sketches

Immersed boundary-conformal isogeometric method for linear elliptic problems

Model-based 3D Face Reconstruction

A Non-Exponential Transmittance Model for Volumetric Scene Representations