196 citations · 591 across the 35 of their papers we have counts for
36 papers
Adaptive Fluid Cohomology on Surfaces
Bastian Abt, David Stotko, Nils Wandel +1
Simulating inviscid, incompressible fluids on non-simply-connected curved surfaces requires careful treatment of the flow's local and global behavior. While recent theoretical adva…
Neu-PiG: Neural Preconditioned Grids for Fast Dynamic Surface Reconstruction on Long Sequences
Julian Kaltheuner, Hannah Dröge, Markus Plack +2
Temporally consistent surface reconstruction of dynamic 3D objects from unstructured point cloud data remains challenging, especially for very long sequences. Existing methods eith…
Transformer-Based Inpainting for Real-Time 3D Streaming in Sparse Multi-Camera Setups
Leif Van Holland, Domenic Zingsheim, Mana Takhsha +4
High-quality 3D streaming from multiple cameras is crucial for immersive experiences in many AR/VR applications. The limited number of views - often due to real-time constraints -…
Moment-Based 3D Gaussian Splatting: Resolving Volumetric Occlusion with Order-Independent Transmittance
Jan U. Müller, Robin Tim Landsgesell, Leif Van Holland +2
The recent success of 3D Gaussian Splatting (3DGS) has reshaped novel view synthesis by enabling fast optimization and real-time rendering of high-quality radiance fields. However,…
Preconditioned Deformation Grids
Julian Kaltheuner, Alexander Oebel, Hannah Droege +2
Dynamic surface reconstruction of objects from point cloud sequences is a challenging field in computer graphics. Existing approaches either require multiple regularization terms o…
SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video
David Stotko, Reinhard Klein
The reconstruction of three-dimensional dynamic scenes is a well-established yet challenging task within the domain of computer vision. In this paper, we propose a novel approach t…
Real-time Image-based Lighting of Glints
Tom Kneiphof, Reinhard Klein
Image-based lighting is a widely used technique to reproduce shading under real-world lighting conditions, especially in real-time rendering applications. A particularly challengin…
Capture Stage Matting: Challenges, Approaches, and Solutions for Offline and Real-Time Processing
Hannah Dröge, Janelle Pfeifer, Saskia Rabich +3
Capture stages are high-end sources of state-of-the-art recordings for downstream applications in movies, games, and other media. One crucial step in almost all pipelines is mattin…
ROSA: Reconstructing Object Shape and Appearance Textures by Adaptive Detail Transfer
Julian Kaltheuner, Patrick Stotko, Reinhard Klein
Reconstructing an object's shape and appearance in terms of a mesh textured by a spatially-varying bidirectional reflectance distribution function (SVBRDF) from a limited set of im…
NeRFs are Mirror Detectors: Using Structural Similarity for Multi-View Mirror Scene Reconstruction with 3D Surface Primitives
Leif Van Holland, Michael Weinmann, Jan U. Müller +2
While neural radiance fields (NeRF) led to a breakthrough in photorealistic novel view synthesis, handling mirroring surfaces still denotes a particular challenge as they introduce…
Metamizer: a versatile neural optimizer for fast and accurate physics simulations
Nils Wandel, Stefan Schulz, Reinhard Klein
Efficient physics simulations are essential for numerous applications, ranging from realistic cloth animations or smoke effects in video games, to analyzing pollutant dispersion in…
Real-Time Rendering of Glints in the Presence of Area Lights
Tom Kneiphof, Reinhard Klein
Many real-world materials are characterized by a glittery appearance. Reproducing this effect in physically based renderings is a challenging problem due to its discrete nature, es…
RHINO-VR Experience: Teaching Mobile Robotics Concepts in an Interactive Museum Exhibit
Erik Schlachhoff, Nils Dengler, Leif Van Holland +4
In 1997, the very first tour guide robot RHINO was deployed in a museum in Germany. With the ability to navigate autonomously through the environment, the robot gave tours to over…
Physics-guided Shape-from-Template: Monocular Video Perception through Neural Surrogate Models
David Stotko, Nils Wandel, Reinhard Klein
3D reconstruction of dynamic scenes is a long-standing problem in computer graphics and increasingly difficult the less information is available. Shape-from-Template (SfT) methods…
TraM-NeRF: Tracing Mirror and Near-Perfect Specular Reflections through Neural Radiance Fields
Leif Van Holland, Ruben Bliersbach, Jan U. Müller +2
Implicit representations like Neural Radiance Fields (NeRF) showed impressive results for photorealistic rendering of complex scenes with fine details. However, ideal or near-perfe…
FPO++: Efficient Encoding and Rendering of Dynamic Neural Radiance Fields by Analyzing and Enhancing Fourier PlenOctrees
Saskia Rabich, Patrick Stotko, Reinhard Klein
Fourier PlenOctrees have shown to be an efficient representation for real-time rendering of dynamic Neural Radiance Fields (NeRF). Despite its many advantages, this method suffers…
Neural inverse procedural modeling of knitting yarns from images
Elena Trunz, Jonathan Klein, Jan Müller +4
We investigate the capabilities of neural inverse procedural modeling to infer high-quality procedural yarn models with fiber-level details from single images of depicted yarn samp…
Efficient 3D Reconstruction, Streaming and Visualization of Static and Dynamic Scene Parts for Multi-client Live-telepresence in Large-scale Environments
Leif Van Holland, Patrick Stotko, Stefan Krumpen +2
Despite the impressive progress of telepresence systems for room-scale scenes with static and dynamic scene entities, expanding their capabilities to scenarios with larger dynamic…
BoundED: Neural Boundary and Edge Detection in 3D Point Clouds via Local Neighborhood Statistics
Lukas Bode, Michael Weinmann, Reinhard Klein
Extracting high-level structural information from 3D point clouds is challenging but essential for tasks like urban planning or autonomous driving requiring an advanced understandi…
Canonical convolutional neural networks
Lokesh Veeramacheneni, Moritz Wolter, Reinhard Klein +1
We introduce canonical weight normalization for convolutional neural networks. Inspired by the canonical tensor decomposition, we express the weight tensors in so-called canonical…
Incomplete Gamma Kernels: Generalizing Locally Optimal Projection Operators
Patrick Stotko, Michael Weinmann, Reinhard Klein
We present incomplete gamma kernels, a generalization of Locally Optimal Projection (LOP) operators. In particular, we reveal the relation of the classical localized estima…
Spline-PINN: Approaching PDEs without Data using Fast, Physics-Informed Hermite-Spline CNNs
Nils Wandel, Michael Weinmann, Michael Neidlin +1
Partial Differential Equations (PDEs) are notoriously difficult to solve. In general, closed-form solutions are not available and numerical approximation schemes are computationall…
Towards Tangible Cultural Heritage Experiences -- Enriching VR-Based Object Inspection with Haptic Feedback
Stefan Krumpen, Reinhard Klein, Michael Weinmann
VR/AR technology is a key enabler for new ways of immersively experiencing cultural heritage artifacts based on their virtual counterparts obtained from a digitization process. In…
Teaching the Incompressible Navier-Stokes Equations to Fast Neural Surrogate Models in 3D
Nils Wandel, Michael Weinmann, Reinhard Klein
Physically plausible fluid simulations play an important role in modern computer graphics and engineering. However, in order to achieve real-time performance, computational speed n…