57 citations · 201 across the 21 of their papers we have counts for
22 papers
Skill-Adaptive Ghost Instructors: Enhancing Retention and Reducing Over-Reliance in VR Piano Learning
Tzu-Hsin Hsieh, Cassandra Michelle Stefanie Visser, Elmar Eisemann +1
Motor-skill learning systems in XR rely on persistent cues. However, constant cueing can induce overreliance and erode memorization and skill transfer. We introduce a skill-adaptiv…
Manifold-Preserving Superpixel Hierarchies and Embeddings for the Exploration of High-Dimensional Images
Alexander Vieth, Boudewijn Lelieveldt, Elmar Eisemann +2
High-dimensional images, or images with a high-dimensional attribute vector per pixel, are commonly explored with coordinated views of a low-dimensional embedding of the attribute…
Surface-Aware Distilled 3D Semantic Features
Lukas Uzolas, Elmar Eisemann, Petr Kellnhofer
Many 3D tasks such as pose alignment, animation, motion transfer, and 3D reconstruction rely on establishing correspondences between 3D shapes. This challenge has recently been app…
Uncertainty for SVBRDF Acquisition using Frequency Analysis
Ruben Wiersma, Julien Philip, Miloš Hašan +4
This paper aims to quantify uncertainty for SVBRDF acquisition in multi-view captures. Under uncontrolled illumination and unstructured viewpoints, there is no guarantee that the o…
MotionDreamer: Exploring Semantic Video Diffusion features for Zero-Shot 3D Mesh Animation
Lukas Uzolas, Elmar Eisemann, Petr Kellnhofer
Animation techniques bring digital 3D worlds and characters to life. However, manual animation is tedious and automated techniques are often specialized to narrow shape classes. In…
Accelerating hyperbolic t-SNE
Martin Skrodzki, Hunter van Geffen, Nicolas F. Chaves-de-Plaza +3
The need to understand the structure of hierarchical or high-dimensional data is present in a variety of fields. Hyperbolic spaces have proven to be an important tool for embedding…