Training and inference of convolutional neural networks (CNNs) on truncated signed distance fields (TSDFs) is a challenging task. Large parts of the scene are usually empty, which makes dense implementations inefficient ...

Debugging or analyzing the performance of global illumination algorithms is a challenging task due to the complex path-scene interaction and numerous places where errors and programming bugs can occur. We present a novel, ...

In multi-label classification, we do not only want to analyze individual data items but also the relationships between the assigned labels. Employing different sources and algorithms, the label assignments differ. We need ...

Comparative analysis of multivariate datasets, e.g. of advanced materials regarding the characteristics of internal structures (fibers, pores, etc.), is of crucial importance in various scientific disciplines. Currently ...

Visualizing the temporal evolution of texts is relevant for many domains that seek to gain insight from text repositories. However, existing visualization methods for text collections do not show fine-grained temporal-thematic ...

This paper presents a framework for generating real-time procedural animations and morphing of 3D point clouds. Point clouds or point-based geometry of varying density can easily be acquired using LiDAR cameras or modern ...

Subdivision surfaces based on bi-quadratic splines have a control net, the DS-net, whose irregularities are n-sided facets. To date their limit shape is poor due to a small footprint of the refinement rules and the difficulty ...