SegNet4D: Efficient Instance-Aware 4D Semantic Segmentation for LiDAR Point Cloud

4D LiDAR semantic segmentation classifies the semantic category of each LiDAR point and detects whether it is dynamic, a critical ability for tasks like obstacle avoidance and autonomous navigation. Existing approaches often rely on computationally heavy 4D convolutions or recursive networks, which...

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Vydané v:	IEEE transactions on automation science and engineering Ročník 22; s. 15339 - 15350
Hlavní autori:	Wang, Neng, Guo, Ruibin, Shi, Chenghao, Wang, Ziyue, Zhang, Hui, Lu, Huimin, Zheng, Zhiqiang, Chen, Xieyuanli
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	IEEE 2025
Predmet:	4D semantic segmentation deep learning Feature extraction Laser radar LiDAR point cloud Motion segmentation moving object segmentation Object segmentation Point cloud compression Real-time systems Robots Semantic segmentation Semantics Three-dimensional displays
ISSN:	1545-5955, 1558-3783
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