LEST: Large-Scale LiDAR Semantic Segmentation With Deployment-Friendly Transformer Architecture

LEST: Large-Scale LiDAR Semantic Segmentation With Deployment-Friendly Transformer Architecture

Large-scale LiDAR-based point cloud semantic segmentation is a critical challenge for autonomous driving perception. Most state-of-the-art LiDAR semantic segmentation methods rely on complex operators, such as sparse 3D convolutions or KdTree structures, which hinder their deployment on modern embed...

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Bibliographic Details
Main Authors: Chuanyu Luo, Nuo Cheng, Sikun Ma, Han Li, Xiaohan Li, Shengguang Lei, Pu Li
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Point cloud semantic segmentation
representation learning
long sequence modeling
linear transformer
model deployment
Online Access:https://ieeexplore.ieee.org/document/10904146/

Internet

https://ieeexplore.ieee.org/document/10904146/

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