← Search

Reinhard Klein

11 accepted papers

2026

Neu-PiG: Neural Preconditioned Grids for Fast Dynamic Surface Reconstruction on Long Sequences

CVPR 2026

Temporally consistent surface reconstruction of dynamic 3D objects from unstructured point cloud data remains challenging, especially for very long sequences. Existing methods either optimize deformations incrementally, risking drift and requiring long runtimes, or rely on complex learned models tha

Cited by 0SourcecodeScholar
2025

Metamizer: A Versatile Neural Optimizer for Fast and Accurate Physics Simulations

ICLR 2025poster

Efficient physics simulations are essential for numerous applications, ranging from realistic cloth animations in video games, to analyzing pollutant dispersion in environmental sciences, to calculating vehicle drag coefficients in engineering applications. Unfortunately, analytical solutions to the…

Cited by 0SourcePDFScholar
2025

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video

ICCV 2025poster

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 that combines the domains of 3D geometry reconstruction and appearance estimation for physically based rendering and pres…

Cited by 0SourcePDFScholar
2024

Physics-guided Shape-from-Template: Monocular Video Perception through Neural Surrogate Models

CVPR 2024poster

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 aim to reconstruct a template-based geometry from RGB images or video sequences often leveraging just a single monocular…

2022

Spline-PINN: Approaching PDEs without Data Using Fast, Physics-Informed Hermite-Spline CNNs

AAAI 2022technical

Partial Differential Equations (PDEs) are notoriously difficult to solve. In general, closed form solutions are not available and numerical approximation schemes are computationally expensive. In this paper, we propose to approach the solution of PDEs based on a novel technique that combines the adv…

2022

Unbiased Gradient Estimation for Differentiable Surface Splatting via Poisson Sampling

ECCV 2022poster

"We propose an efficient and GPU-accelerated sampling framework which enables unbiased gradient approximation for differentiable point cloud rendering based on surface splatting. Our framework models the contribution of a point to the rendered image as a probability distribution. We derive an unbias…

2021

Learning Incompressible Fluid Dynamics from Scratch - Towards Fast, Differentiable Fluid Models that Generalize

ICLR 2021spotlight

Fast and stable fluid simulations are an essential prerequisite for applications ranging from computer-generated imagery to computer-aided design in research and development. However, solving the partial differential equations of incompressible fluids is a challenging task and traditional numerical…

2019

A VR System for Immersive Teleoperation and Live Exploration with a Mobile Robot

IROS 2019poster

Applications like disaster management and industrial inspection often require experts to enter contaminated places. To circumvent the need for physical presence, it is desirable to generate a fully immersive individual live teleoperation experience. However, standard video-based approaches suffer fr…

Cited by 135SourceScholar
2019

Inverse Procedural Modeling of Knitwear

CVPR 2019oral

The analysis and modeling of cloth has received a lot of attention in recent years. While recent approaches are focused on woven cloth, we present a novel practical approach for the inference of more complex knitwear structures as well as the respective knitting instructions from only a single image…

Cited by 11PDFScholar