Recent publications

November 2024

Gaussian Splatting Decoder for 3D-aware Generative Adversarial Networks

Florian Tim Barthel, Peter Eisert, Anna Hilsmann, Wieland Morgenstern, Arian Beckmann

We present a novel approach that combines the high rendering quality of NeRF-based 3D-aware GANs with the flexibility and computational advantages of 3DGS. By training a decoder that maps implicit NeRF representations to explicit 3D Gaussian...


November 2024

Experimental Characterization of a WR3-Coupled Photodiode Transmitter for High-Speed Terahertz Wireless Communication

In-Ho Baek, Patrick Runge, Martin Schell, Felix Ganzer, Colja Schubert, Ronald Freund, Robert Elschner, Oliver Stiewe, Alexander Schindler, Jonas Gläsel, Metin Furkan Ulukan, Trung T. Tran

We analyze the system performance of a large bandwidth photonic THz transmitter based on a WR3 coupled photodiode. Employing probabilistic constellation shaping (PCS) alongside a 64-QAM base constellation, we achieve net data rates of up to 76.8...


November 2024

Multi-Resolution Generative Modeling of Human Motion from Limited Data

David Moreno-Villamarin, Peter Eisert, Anna Hilsmann

We present a generative model that learns to synthesize human motion from limited training sequences. Our framework provides conditional generation and blending across multiple temporal resolutions. moOurdel adeptly captures human motion patterns...


November 2024

Robust mmWave/sub-THz multi-connectivity using minimal coordination and coarse synchronization

Lorenzo Miretti, Slawomir Stanczak, Giuseppe Caire

How to provide robust connectivity against signal blockage in 6G mmWave/sub-THz networks? This study demonstrates that carefully designed multi-connectivity schemes can realize full macrodiversity gains and significant SNR gains through canonical...


November 2024

Real-time Experiments towards an Automotive OFDMA Communication Bus

Matthias Koepp, Volker Jungnickel, Kai Habel

We present a new automotive bus system which allows enhanced channel adaptation and fine-granular multi-user access based on OFDMA. We highlight advantages of OFDMA in automotive applications, sketch the concept and present an FPGA prototype.


October 2024

Time Adaptive Probabilistic Shaping for Combined Optical/THz Links

In-Ho Baek, Colja Schubert, Ronald Freund, Robert Elschner, Frederik Bart, Fred Meier, David Hellmann, Andreas Maaßen

We investigate the applicability of PAS for outdoor THz wireless links in simulations with weather-dependent loss models. Link performances are evaluated and optimal shaping entropies are determined to adjust error rates to a given FEC threshold....


October 2024

Experimental Dataset for Developing and Testing ML Models in Optical Communication Systems

Caio Marciano Santos, Colja Schubert, Johannes Fischer, Robert Emmerich, Mohammad Behnam Shariati, Pooyan Safari, Abdelrahmane Moawad

We present here a public dataset for developing and testing ML models. The dataset is developed in a laboratory setting and includes 12672 samples including data points with different modulation formats, symbol rates, distances, WDM channel...


October 2024

Causes of Outcome Learning: A causal inference-inspired machine learning approach to disentangling common combinations of potential causes of a health outcome

Andreas Rieckmann, Wojciech Samek, Sebastian Lapuschkin, Leila Arras, Piotr Dworzynski, Onyebuchi A. Arah, Naja H. Rod, Claus T. Ekstrom

Nearly all diseases are caused by different combinations of exposures. We present the Causes of Outcome Learning approach (CoOL), which seeks to discover combinations of exposures that lead to an increased risk of a specific outcome in parts of...


October 2024

SPVLoc: Semantic Panoramic Viewport Matching for 6D Camera Localization in Unseen Environments

Niklas Gard, Peter Eisert, Anna Hilsmann

We present SPVLoc, a global indoor localization method that accurately determines the six-dimensional (6D) camera pose of a query image and requires minimal scene-specific prior knowledge and no scene-specific training. Our approach employs a...


October 2024

Compact 3D Scene Representation via Self-Organizing Gaussian Grids

Wieland Morgenstern, Peter Eisert, Anna Hilsmann, Florian Tim Barthel

We introduce a compact scene representation organizing the parameters of 3D Gaussian Splatting (3DGS) into a 2D grid with local homogeneity, ensuring a drastic reduction in storage requirements without compromising visual quality during...


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