4 citations · 7 across the 5 of their papers we have counts for
6 papers
WayveScenes101: A Dataset and Benchmark for Novel View Synthesis in Autonomous Driving
Jannik Zürn, Paul Gladkov, Sofía Dudas +5
We present WayveScenes101, a dataset designed to help the community advance the state of the art in novel view synthesis that focuses on challenging driving scenes containing many…
AutoGraph: Predicting Lane Graphs from Traffic Observations
Jannik Zürn, Ingmar Posner, Wolfram Burgard
Lane graph estimation is a long-standing problem in the context of autonomous driving. Previous works aimed at solving this problem by relying on large-scale, hand-annotated lane g…
TrackletMapper: Ground Surface Segmentation and Mapping from Traffic Participant Trajectories
Jannik Zürn, Sebastian Weber, Wolfram Burgard
Robustly classifying ground infrastructure such as roads and street crossings is an essential task for mobile robots operating alongside pedestrians. While many semantic segmentati…
Self-Supervised Moving Vehicle Detection from Audio-Visual Cues
Jannik Zürn, Wolfram Burgard
Robust detection of moving vehicles is a critical task for any autonomously operating outdoor robot or self-driving vehicle. Most modern approaches for solving this task rely on tr…
Lane Graph Estimation for Scene Understanding in Urban Driving
Jannik Zürn, Johan Vertens, Wolfram Burgard
Lane-level scene annotations provide invaluable data in autonomous vehicles for trajectory planning in complex environments such as urban areas and cities. However, obtaining such…
HeatNet: Bridging the Day-Night Domain Gap in Semantic Segmentation with Thermal Images
Johan Vertens, Jannik Zürn, Wolfram Burgard
The majority of learning-based semantic segmentation methods are optimized for daytime scenarios and favorable lighting conditions. Real-world driving scenarios, however, entail ad…