App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 5

Multi-scale and dual-modality fusion for LiDAR point cloud semantic segmentation

Lu Bin1,2
Shang Guodong1,2
1. Dept. of Computer Science, North China Electric Power University, Baoding Hebei 071003, China
2. Key Laboratory of Energy and Electric Power Knowledge Calculation in Hebei Province, Hebei Baoding 071003, China
DOI: 10.19734/j.issn.1001-3695.2025.08.0369

Abstract

To address the problem of spatial structure information loss in LiDAR point cloud semantic segmentation using 2D projection methods, a segmentation approach integrating multi-scale perception and dual-modal interaction was proposed. A multi-scale convolution module (MSConv) was designed to extract hierarchical semantic features from projected point clouds using depthwise separable convolutions and multi-branch structures with low computational cost. A dual-modal fusion module (DMF) was then introduced to achieve deep coupling between 3D geometric structures and 2D contextual information through bidirectional graph-point mapping, enhancing structural integrity and semantic consistency. Furthermore, a residual contrastive attention fusion module (RC-TFAM) was employed to adaptively refine the fused features from both modalities. Experimental results on the SemanticKITTI and SemanticPOSS datasets show that the proposed method achieved mIoU scores of 67.8% and 54.8%, respectively. The results demonstrate that this method maintains high computational efficiency while exhibiting strong structural modeling and cross-modal semantic fusion capabilities.

Foundation Support

北京自然科学基金资助项目(4254105)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.08.0369
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 5

Publish History

[2026-01-08] Accepted Paper

Cite This Article

鲁斌, 尚国栋. 基于多尺度感知和双模态融合的激光雷达点云语义分割 [J]. 计算机应用研究, 2026, 43 (5). (2026-01-20). https://doi.org/10.19734/j.issn.1001-3695.2025.08.0369. (Lu Bin, Shang Guodong. Multi-scale and dual-modality fusion for LiDAR point cloud semantic segmentation [J]. Application Research of Computers, 2026, 43 (5). (2026-01-20). https://doi.org/10.19734/j.issn.1001-3695.2025.08.0369. )

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  • Application Research of Computers Monthly Journal
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    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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