Publications associées à Better Patch Stitching for Parametric Surface Reconstruction

Publications associées (44)

Customizing the human-avatar mapping based on EEG error related potentials during avatar-based interaction

Olaf Blanke, José del Rocio Millán Ruiz, Ronan Boulic, Ricardo Andres Chavarriaga Lozano, Bruno Herbelin, Fumiaki Iwane, Thibault Serge Mario Porssut

Objective. A key challenge of virtual reality (VR) applications is to maintain a reliable human-avatar mapping. Users may lose the sense of controlling (sense of agency), owning (sense of body ownership), or being located (sense of self-location) inside th ...

2024

Aggregating Spatial and Photometric Context for Photometric Stereo

David Honzátko

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 ...

EPFL2024

SAT-based Exact Modulo Scheduling Mapping for Resource-Constrained CGRAs

David Atienza Alonso, Giovanni Ansaloni, José Angel Miranda Calero, Benoît Walter Denkinger, Juan Pablo Sapriza Araujo, Ruben Rodriguez, Rubén Rodríguez Álvarez

Coarse-Grain Reconfigurable Arrays (CGRAs) represent emerging low-power architectures designed to accelerate Compute-Intensive Loops (CILs). The effectiveness of CGRAs in providing acceleration relies on the quality of mapping: how efficiently the CIL is c ...

2024

Adaptive Robust Data-Driven Building Control via Bilevel Reformulation: An Experimental Result

Colin Neil Jones, Yingzhao Lian, Jicheng Shi, Manuel Pascal Koch

Data-driven control approaches for the minimization of energy consumption of buildings have the potential to significantly reduce deployment costs and increase the uptake of advanced control in this sector. A number of recent approaches based on the applic ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

The nature of carbon deposits and their formation pathways during catalytic supercritical water gasification of glycerol

Christopher Marc Hunston

Supercritical water gasification (SCWG) is a promising technology to convert wet biomass to renewable natural gas. The present study sheds light on the chemical composition and the formation mechanism of coke deposits on a Ru/CNF catalyst during continuous ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2023

Technology Mapping Using Multi-output Library Cells

Giovanni De Micheli, Alessandro Tempia Calvino

Technology mapping transforms a technology-independent representation into a technology-dependent one given a library of cells. Even if technology libraries contain multi-output cells, state-of-the-art techniques fully exploit single-output cells only. Mul ...

2023

Practice of Streaming Processing of Dynamic Graphs: Concepts, Models, and Systems

Mikhail Kapralov

Graphs processing has become an important part of various areas of computing, including machine learning, medical applications, social network analysis, computational sciences, and others. A growing amount of the associated graph processing workloads are d ...

2023

Automatic Parameterization for Aerodynamic Shape Optimization via Deep Geometric Learning

Pascal Fua, Zhen Wei

We propose two deep learning models that fully automate shape parameterization for aerodynamic shape optimization. Both models are optimized to parameterize via deep geometric learning to embed human prior knowledge into learned geometric patterns, elimina ...

2023

Steel Sheet Sheathed Cold-Formed Steel Framed In-line Wall Systems. II: Impact of Nonstructural Detailing

Fani Derveni

Although cold-formed steel (CFS) framing systems have the potential to support the need for resilient housing, the use of CFS has been restricted due to gaps in understanding its structural behavior and by the limited guidelines provided in design standard ...

ASCE-AMER SOC CIVIL ENGINEERS2022

Deep transfer learning of additive manufacturing mechanisms across materials in metal-based laser powder bed fusion process

Roland Logé, Rita Drissi Daoudi

The defective regimes in metal-based Laser Powder Bed Fusion (LPBF) processes can be minimized by deploying in-situ monitoring strategies comprising Machine learning (ML) algorithms and sensing techniques. So far, algorithms trained for monitoring a partic ...

ELSEVIER SCIENCE SA2022

Low-damage steel structures for enhanced life-cycle seismic performance

Dimitrios Lignos, Martina Paronesso

During an earthquake, steel frame buildings with bracings are prone to high absolute floor acceleration demands, thereby causing damage to acceleration-sensitive non-structural elements and building content. Inelastic deformations in steel bracings and/or ...

ERNST & SOHN2022

A Versatile Mapping Approach for Technology Mapping and Graph Optimization

Giovanni De Micheli, Heinz Riener, Alessandro Tempia Calvino, Akash Kumar

This paper proposes a versatile mapping approach that has three objectives: i) it can map from one technology-independent graph representation to another; ii) it can map to a cell library; iii) it supports logic rewriting. The method is cut-based, mitigate ...

IEEE2022

Effect of Y2O3 dispersoids on microstructure and creep properties of Hastelloy X processed by laser powder-bed fusion

Christian Leinenbach

Laser powder bed fusion (LPBF) was used to consolidate powders of a Ni-Cr-Fe-Mo alloy (Hastelloy X) blended with 1 wt% Y2O3 nanometric powders. The nearly-dense, crack-free specimens, with and without oxide dispersion strengthening (ODS), exhibit high-aspe ...

ELSEVIER2022

Slim: Explicit Slot-Intent Mapping With Bert For Joint Multi-Intent Detection And Slot Filling

Boi Faltings, Fei Mi

Utterance-level intent detection and token-level slot filling are two key tasks for spoken language understanding (SLU) in task-oriented systems. Most existing approaches assume that only a single intent exists in an utterance. However, there are often mul ...

IEEE2022

Learning to Represent and Reconstruct 3D Deformable Objects

Jan Bednarík

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 ...

EPFL2022

Image-based geometric digital twinning for stone masonry elements

Katrin Beyer, Bryan German Pantoja Rosero, Savvas Saloustros

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 ...

2022

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

Omnidirectional Strategies for Exploring Ancient Cities and Territories

Sarah Irene Brutton Kenderdine

By focusing on technologies of virtual reality in conjunction with theories of “place” and “presence,” this chapter outlines the importance of new approaches to the museological experience and exploration of ancient cities and cultural heritage sites. Expl ...

Oxford University Press2020

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

Mapping quality prediction for RTK/PPK-equipped micro-drones operating in complex natural environment

Jan Skaloud, Davide Antonio Cucci, Emmanuel Pierre Quentin Clédat, Laurent Valentin Jospin

Drone mapping with GNSS-assisted photogrammetry is a highly efficient method for surveying small -or medium- sized areas. However, the mapping quality is not intuitively predictable, particularly in complex environments (with steep and cluttered terrain), ...

2020