We present a modeling framework designed for patient-specific computational
hemodynamics to be performed in the context of large-scale studies. The framework takes …

In many areas of industry, it is desirable to create geometric models of existing objects for
which no such model is available. This paper reviews the process of reverse engineering of …

Abstract Neural Radiance Fields (NeRFs) have achieved great success in the past few
years. However, most current methods still require intensive resources due to ray marching …

Recent works in geometric deep learning have introduced neural networks that allow
performing inference tasks on three-dimensional geometric data by defining convolution …

Engineering laboratory courses have a significant role in building practical knowledge and
enhancing the skills of the students. While working in electronics laboratories, students often …

Humans perceive the three-dimensional structure of the world with apparent ease. However,
despite all of the recent advances in computer vision research, the dream of having a …

We describe and demonstrate an algorithm that takes as input an unorganized set of points
{xl,.... xn}⊂ R3 on or near an unknown manifold M, and produces as output a simplicial …

This paper proposes a novel algorithm for multiview stereopsis that outputs a dense set of
small rectangular patches covering the surfaces visible in the images. Stereopsis is …

Many applications in computer graphics require complex, highly detailed models. However,
the level of detail actually necessary may vary considerably. To control processing time, it is …

This fifth edition has been fully updated to cover the many advances made in CAGD and
curve and surface theory since 1997, when the fourth edition appeared. Material has been …