Fast 3D Modeling of Prosthetic Robotic Hands Based on a Multi-Layer Deformable Design
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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 ...
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 ...
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 ...
2023
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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 ...
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 pro ...
Deep implicit surfaces excel at modeling generic shapes but do not always capture the regularities present in manufactured objects, which is something simple geometric primitives are particularly good at. In this paper, we propose a representation combinin ...
The use of soft and stretchable materials allows the development of adaptive robotic systems and human-machine interfaces that are more natural and comfortable to interact with. One of the application fields that benefits the most from these compliant mate ...
In the modern age of miniaturisation, Smart Materials, a type of material that reacts mechanically to a certain stimulus, have become an integral part of this revolution. Among these materials, Shape Memory Alloys (SMAs), which have the highest volumetric ...
EPFL2022
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 ...
In this work we perform a neutron Bragg edge tomography of stainless steel 316L additive manufacturing samples, one as built via standard laser powder bed fusion, and one using the novel three-dimensional (3D) laser shock peening technique. First, we consi ...