A Novel Vision Transformer for Camera-LiDAR Fusion Based Traffic Object Segmentation

Toomas Tahves; Junyi Gu; Junyi Gu; Mauro Bellone; Raivo Sell

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Paper

A Novel Vision Transformer for Camera-LiDAR Fusion Based Traffic Object Segmentation

Topics: Autonomous Systems; Big Data; Data Science; Deep Learning; Machine Learning; Neural Networks; Robot and Multi-Robot Systems; Vision and Perception

In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, 566-573, 2025 , Porto, Portugal

Authors: Toomas Tahves ¹ ; Junyi Gu ^{1

;

2} ; Mauro Bellone ³ and Raivo Sell ¹

Affiliations: ¹ Department of Mechanical and Industrial Engineering, Tallinn University of Technology, Estonia ; ² Dept. of Computer Science and Engineering, Chalmers University of Technology and University of Gothenburg, Sweden ; ³ FinEst Centre for Smart Cities, Tallinn University of Technology, Estonia

Keyword(s): Dense Vision Transformers, Semantic Segmentation, Sensor Fusion, Residual Neural Network.

Abstract: This paper presents Camera-LiDAR Fusion Transformer (CLFT) models for traffic object segmentation, which leverage the fusion of camera and LiDAR data using vision transformers. Building on the methodology of visual transformers that exploit the self-attention mechanism, we extend segmentation capabilities with additional classification options to a diverse class of objects including cyclists, traffic signs, and pedestrians across diverse weather conditions. Despite good performance, the models face challenges under adverse conditions which underscores the need for further optimization to enhance performance in darkness and rain. In summary, the CLFT models offer a compelling solution for autonomous driving perception, advancing the state-of-the-art in multimodal fusion and object segmentation, with ongoing efforts required to address existing limitations and fully harness their potential in practical deployments.

CC BY-NC-ND 4.0

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Paper citation in several formats:

Tahves, T., Gu, J., Bellone, M. and Sell, R. (2025). A Novel Vision Transformer for Camera-LiDAR Fusion Based Traffic Object Segmentation. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-758-737-5; ISSN 2184-433X, SciTePress, pages 566-573. DOI: 10.5220/0013239000003890

@conference{icaart25,
author={Toomas Tahves and Junyi Gu and Mauro Bellone and Raivo Sell},
title={A Novel Vision Transformer for Camera-LiDAR Fusion Based Traffic Object Segmentation},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2025},
pages={566-573},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013239000003890},
isbn={978-989-758-737-5},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - A Novel Vision Transformer for Camera-LiDAR Fusion Based Traffic Object Segmentation
SN - 978-989-758-737-5
IS - 2184-433X
AU - Tahves, T.
AU - Gu, J.
AU - Bellone, M.
AU - Sell, R.
PY - 2025
SP - 566
EP - 573
DO - 10.5220/0013239000003890
PB - SciTePress