Better Patch Stitching for Parametric Surface Reconstruction

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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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 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 ...

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 ...

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 ...

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 ...

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), ...

Better Patch Stitching for Parametric Surface Reconstruction

Chattez avec Graph Search

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

Aggregating Spatial and Photometric Context for Photometric Stereo

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

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

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

Technology Mapping Using Multi-output Library Cells

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

Automatic Parameterization for Aerodynamic Shape Optimization via Deep Geometric Learning

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

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

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

A Versatile Mapping Approach for Technology Mapping and Graph Optimization

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

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

Learning to Represent and Reconstruct 3D Deformable Objects

Image-based geometric digital twinning for stone masonry elements

Differentiable Signed Distance Function Rendering

Omnidirectional Strategies for Exploring Ancient Cities and Territories

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

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