115 citations · 313 across the 18 of their papers we have counts for
18 papers
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…
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…
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…
Occlusion Fields: An Implicit Representation for Non-Line-of-Sight Surface Reconstruction
Javier Grau, Markus Plack, Patrick Haehn +2
Non-line-of-sight reconstruction (NLoS) is a novel indirect imaging modality that aims to recover objects or scene parts outside the field of view from measurements of light that i…