3 papers
cs.CV2026
Leveraging Previous-Traversal Point Cloud Map Priors for Camera-Based 3D Object Detection and Tracking
Markus Käppeler, Ãzgün Ãiçek, Yakov Miron +1
Camera-based 3D object detection and tracking are central to autonomous driving, yet precise 3D object localization remains fundamentally constrained by depth ambiguity when no exp…
cs.CV2025
Bridging Perspectives: Foundation Model Guided BEV Maps for 3D Object Detection and Tracking
Markus Käppeler, Ãzgün Ãiçek, Daniele Cattaneo +3
Camera-based 3D object detection and tracking are essential for perception in autonomous driving. Current state-of-the-art approaches often rely exclusively on either perspective-v…
cs.RO2024
A Good Foundation is Worth Many Labels: Label-Efficient Panoptic Segmentation
Niclas Vödisch, Kürsat Petek, Markus Käppeler +2
A key challenge for the widespread application of learning-based models for robotic perception is to significantly reduce the required amount of annotated training data while achie…