Closed-Form Solution to Non-rigid 3D Surface Registration

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This study explores the 4D reconstruction of part of the monumental heritage of St. Mark’s Square in Venice, contextualizing the modeling of its evolution in the broader field of digital historiography. The presented methodology is based on comparing the p ...

We present GigaPose, a fast, robust, and accurate method for CAD-based novel object pose estimation in RGB images. GigaPose first leverages discriminative "templates", rendered images of the CAD models, to recover the out-of-plane rotation and then uses pa ...

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 ...

The optical domain presents potential avenues for enhancing both computing and communication due to its inherent properties of bandwidth, parallelism, and energy efficiency. This research focuses on harnessing 3-Dimensional (3D) diffractive optics for nove ...

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 ...

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 ...

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 ...

To obtain a more complete understanding of material microstructure at the nanoscale and to gain profound insights into their properties, there is a growing need for more efficient and precise methods that can streamline the process of 3D imaging using a tr ...

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 ...

3D reconstruction of deformable (or non-rigid) scenes from a set of monocular 2D image observations is a long-standing and actively researched area of computer vision and graphics. It is an ill-posed inverse problem, since-without additional prior assumpti ...

Metal plasticity is an inherently multiscale phenomenon due to the complex long-range field of atomistic dislocations that are the primary mechanism for plastic deformation in metals. Atomistic/Continuum (A/C) coupling methods are computationally efficient ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

Tim-domain near-infrared optical tomography (TD NIROT) techniques based on diffuse light were gaining performance over the last years. They are capable of imaging tissue at several centimeters depth and reveal clinically relevant information, such as tissu ...

Closed-Form Solution to Non-rigid 3D Surface Registration

Chattez avec Graph Search

Reconstructing Saint Mark’s Square in Venice: A 4D Model with Point Cloud Integration for Analyzing Historiographical Hypotheses

GigaPose: Fast and Robust Novel Object Pose Estimation via One Correspondence

Semantic Shape Editing with Parametric Implicit Templates

Aggregating Spatial and Photometric Context for Photometric Stereo

3D diffractive optics for linear interconnects and nonlinear processing

Deep Learning for 3D Surface Modelling and Reconstruction

ISP: Multi-Layered Garment Draping with Implicit Sewing Patterns

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

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

3D reconstruction of curvilinear one-dimensional objects viewed in transmission electron microscopy

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

State of the Art in Dense Monocular Non-Rigid 3D Reconstruction

Lattice Green's function method for Atomistic/Continuum coupling

Robust Isometric Non-Rigid Structure-From-Motion

Image-based geometric digital twinning for stone masonry elements

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

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

Learning to Represent and Reconstruct 3D Deformable Objects

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

2.5 Hz sample rate time-domain near-infrared optical tomography based on SPAD-camera image tissue hemodynamics