4 papers
Beam-Wise Statistical Background Subtraction for Static Roadside LiDAR: A Cross-Sensor Benchmark Study
Alexander Baumann, Marcel Vosshans, Thao Dang
Background subtraction is a key preprocessing step for infrastructure-based LiDAR perception, enabling efficient isolation of dynamic traffic participants without semantic annotati…
StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception
Marcel Vosshans, Omar Ait-Aider, Youcef Mezouar +1
This paper presents StixelNExT++, a novel approach to scene representation for monocular perception systems. Building on the established Stixel representation, our method infers 3D…
StixelNExT: Toward Monocular Low-Weight Perception for Object Segmentation and Free Space Detection
Marcel Vosshans, Omar Ait-Aider, Youcef Mezouar +1
In this work, we present a novel approach for general object segmentation from a monocular image, eliminating the need for manually labeled training data and enabling rapid, straig…
CoopScenes: Multi-Scene Infrastructure and Vehicle Data for Advancing Collective Perception in Autonomous Driving
Marcel Vosshans, Alexander Baumann, Matthias Drueppel +4
The increasing complexity of urban environments has underscored the potential of effective collective perception systems. To address these challenges, we present the CoopScenes dat…