In this work, we adapt and improve recent isotropic material estimation efforts to estimate spatially varying anisotropic materials with an additional Fresnel term using a variable set of input images and are able to handle ...

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 ...

We propose a real-time technique for rendering Gaussian-Product subdivision surfaces. This is achieved by our real-time subdivision pipeline, able to accept the base of Gaussian-Product subdivision, that is, a covariance ...

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 ...

Visual analysis of multidimensional data commonly involves dimensionality reduction to project the data samples into a lowerdimensional visual space. Star coordinates (SC) provide a means to explore the multidimensional ...

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 ...

Subdivision solids, such as Catmull-Clark (CC) solids, are versatile volumetric representation schemes that can be employed for geometric modeling, physically based simulation, and multi-material additive manufacturing. ...

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 ...