5 citations · 9 across the 11 of their papers we have counts for
11 papers
Invascal: Inverse-Vacuity Self-Calibration for Uncertainty-Aware LiDAR Range-View Semantic Segmentation
Kerim Turacan, Hannes Reichert, Andrei Bolandut +1
LiDAR semantic segmentation is a core perception capability for autonomous vehicles and mobile robots. However, safe operation also depends on knowing when predictions are unreliab…
DD-MDN: Human Trajectory Forecasting with Diffusion-Based Dual Mixture Density Networks and Uncertainty Self-Calibration
Manuel Hetzel, Kerim Turacan, Hannes Reichert +2
Human Trajectory Forecasting (HTF) predicts future human movements from past trajectories and environmental context, with applications in Autonomous Driving, Smart Surveillance, an…
LiDAR Based Semantic Perception for Forklifts in Outdoor Environments
Benjamin Serfling, Hannes Reichert, Lorenzo Bayerlein +2
In this study, we present a novel LiDAR-based semantic segmentation framework tailored for autonomous forklifts operating in complex outdoor environments. Central to our approach i…
Real Time Semantic Segmentation of High Resolution Automotive LiDAR Scans
Hannes Reichert, Benjamin Serfling, Elijah Schüssler +3
In recent studies, numerous previous works emphasize the importance of semantic segmentation of LiDAR data as a critical component to the development of driver-assistance systems a…
Reliable Probabilistic Human Trajectory Prediction for Autonomous Applications
Manuel Hetzel, Hannes Reichert, Konrad Doll +1
Autonomous systems, like vehicles or robots, require reliable, accurate, fast, resource-efficient, scalable, and low-latency trajectory predictions to get initial knowledge about f…
Height Change Feature Based Free Space Detection
Steven Schreck, Hannes Reichert, Manuel Hetzel +2
In the context of autonomous forklifts, ensuring non-collision during travel, pick, and place operations is crucial. To accomplish this, the forklift must be able to detect and loc…
Smart Infrastructure: A Research Junction
Manuel Hetzel, Hannes Reichert, Konrad Doll +1
Complex inner-city junctions are among the most critical traffic areas for injury and fatal accidents. The development of highly automated driving (HAD) systems struggles with the…
The IMPTC Dataset: An Infrastructural Multi-Person Trajectory and Context Dataset
Manuel Hetzel, Hannes Reichert, Günther Reitberger +3
Inner-city intersections are among the most critical traffic areas for injury and fatal accidents. Automated vehicles struggle with the complex and hectic everyday life within thos…
Sensor Equivariance by LiDAR Projection Images
Hannes Reichert, Manuel Hetzel, Steven Schreck +2
In this work, we propose an extension of conventional image data by an additional channel in which the associated projection properties are encoded. This addresses the issue of sen…
Towards Sensor Data Abstraction of Autonomous Vehicle Perception Systems
Hannes Reichert, Lukas Lang, Kevin Rösch +6
Full-stack autonomous driving perception modules usually consist of data-driven models based on multiple sensor modalities. However, these models might be biased to the sensor setu…
Cyclist Intention Detection: A Probabilistic Approach
Stefan Zernetsch, Hannes Reichert, Viktor Kress +2
This article presents a holistic approach for probabilistic cyclist intention detection. A basic movement detection based on motion history images (MHI) and a residual convolutiona…