collaborators

7 papers

cs.GR2026

Feature-Guided Diffusion for Non-Differentiable Inverse Rendering

Andrei-Timotei Ardelean, Michael Fischer, Tim Weyrich +1

Inverse rendering is traditionally solved via differentiable renderers and gradient descent, which requires substantial problem-specific engineering and is prone to getting stuck i…

eess.IV2025

MAROON: A Dataset for the Joint Characterization of Near-Field High-Resolution Radio-Frequency and Optical Depth Imaging Techniques

Vanessa Wirth, Johanna Bräunig, Nikolai Hofmann +3

Utilizing the complementary strengths of wavelength-specific range or depth sensors is crucial for robust computer-assisted tasks such as autonomous driving. Despite this, there is…

eess.SP2025

MM-2FSK: Multimodal Frequency Shift Keying for Ultra-Efficient and Robust High-Resolution MIMO Radar Imaging

Vanessa Wirth, Johanna Bräunig, Martin Vossiek +2

Accurate reconstruction of static and rapidly moving targets demands three-dimensional imaging solutions with high temporal and spatial resolution. Radar sensors are a promising se…

cs.CV2025

Example-Based Feature Painting on Textures

Andrei-Timotei Ardelean, Tim Weyrich

In this work, we propose a system that covers the complete workflow for achieving controlled authoring and editing of textures that present distinctive local characteristics. These…

cs.CV2025

Quantized FCA: Efficient Zero-Shot Texture Anomaly Detection

Andrei-Timotei Ardelean, Patrick Rückbeil, Tim Weyrich

Zero-shot anomaly localization is a rising field in computer vision research, with important progress in recent years. This work focuses on the problem of detecting and localizing…

cs.CV2025

FruitNeRF++: A Generalized Multi-Fruit Counting Method Utilizing Contrastive Learning and Neural Radiance Fields

Lukas Meyer, Andrei-Timotei Ardelean, Tim Weyrich +1

We introduce FruitNeRF++, a novel fruit-counting approach that combines contrastive learning with neural radiance fields to count fruits from unstructured input photographs of orch…