In recent years, Convolutional Neural Networks (CNN) have proven to be efficient analysis tools for processing point clouds, e.g., for reconstruction, segmentation, and classification. In this article, we focus on the classification of edges in point clouds, w...

Representing complex 3D objects as simple geometric primitives, known as shape abstraction, is important for geometric modeling, structural analysis, and shape synthesis. In this paper, we propose an unsupervised shape abstraction method to map a point cloud i...

We propose a new method that reconstructs 3D human motion from in-the-wild video by making full use of prior knowledge on the laws of physics. Previous studies focus on reconstructing joint angles and positions in the body local coordinate frame. Body translat...

We present a caricature generation framework based on shape and style manipulation using StyleGAN. Our framework, dubbed StyleCariGAN , automatically creates a realistic and detailed caricature from an input photo with optional controls on shape exaggeration d...

High-quality denoising of Monte Carlo low-sample renderings remains a critical challenge for practical interactive ray tracing. We present a new learning-based denoiser that achieves state-of-the-art quality and runs at interactive rates. Our model processes i...

We present TreePartNet , a neural network aimed at reconstructing tree geometry from point clouds obtained by scanning real trees. Our key idea is to learn a natural neural decomposition exploiting the assumption that a tree comprises locally cylindrical shape...

Time-correlated imaging is an emerging sensing modality that has been shown to enable promising application scenarios, including lidar ranging, fluorescence lifetime imaging, and even non-line-of-sight sensing. A leading technology for obtaining time-correlate...

Turbomachinery design is increasingly carried out by means of automated workflows based on high-fidelity physical models and optimization algorithms. The parametrization of the blade geometry is an essential aspect of such workflows because it defines the desi...

This paper introduces a novel geometric multigrid solver for unstructured curved surfaces. Multigrid methods are highly efficient iterative methods for solving systems of linear equations. Despite the success in solving problems defined on structured domains, ...

CNC machining is the leading subtractive manufacturing technology. Although it is in use since decades, it is far from fully solved and still a rich source for challenging problems in geometric computing. We demonstrate this at hand of 5-axis machining of free...