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Authors: Maik Steinhauser ; Laurenz Reichardt ; Nikolas Ebert and Oliver Wasenmüller

Affiliation: Mannheim University of Applied Sciences, Germany

Keyword(s): Lidar, Point Cloud, Panoptic, Segmentation, 3D, Deep Learning, AI.

Abstract: This paper introduces a novel approach to 4D Panoptic LiDAR Segmentation that decouples semantic and instance segmentation, leveraging single-scan semantic predictions as prior information for instance segmentation. Our method D-PLS first performs single-scan semantic segmentation and aggregates the results over time, using them to guide instance segmentation. The modular design of D-PLS allows for seamless integration on top of any semantic segmentation architecture, without requiring architectural changes or retraining. We evaluate our approach on the SemanticKITTI dataset, where it demonstrates significant improvements over the baseline in both classification and association tasks, as measured by the LiDAR Segmentation and Tracking Quality (LSTQ) metric. Furthermore, we show that our decoupled architecture not only enhances instance prediction but also surpasses the baseline due to advancements in single-scan semantic segmentation.

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Paper citation in several formats:
Steinhauser, M., Reichardt, L., Ebert, N. and Wasenmüller, O. (2025). D-PLS: Decoupled Semantic Segmentation for 4D-Panoptic-LiDAR-Segmentation. In Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP; ISBN 978-989-758-728-3; ISSN 2184-4321, SciTePress, pages 645-650. DOI: 10.5220/0013114900003912

@conference{visapp25,
author={Maik Steinhauser and Laurenz Reichardt and Nikolas Ebert and Oliver Wasenmüller},
title={D-PLS: Decoupled Semantic Segmentation for 4D-Panoptic-LiDAR-Segmentation},
booktitle={Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP},
year={2025},
pages={645-650},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013114900003912},
isbn={978-989-758-728-3},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP
TI - D-PLS: Decoupled Semantic Segmentation for 4D-Panoptic-LiDAR-Segmentation
SN - 978-989-758-728-3
IS - 2184-4321
AU - Steinhauser, M.
AU - Reichardt, L.
AU - Ebert, N.
AU - Wasenmüller, O.
PY - 2025
SP - 645
EP - 650
DO - 10.5220/0013114900003912
PB - SciTePress

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