Leveraging Smooth Deformation Augmentation for LiDAR Point Cloud Semantic Segmentation-Reference-Cited by-同舟云学术

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Leveraging Smooth Deformation Augmentation for LiDAR Point Cloud Semantic Segmentation

Published:2024-02 Issue:2 Volume:9 Page:3316-3329
ISSN:2379-8904
Container-title:IEEE Transactions on Intelligent Vehicles
language:
Short-container-title:IEEE Trans. Intell. Veh.

Author:

Qiu Shoumeng¹^ORCID,Chen Jie¹^ORCID,Lai Chenghang¹^ORCID,Lu Hong¹^ORCID,Xue Xiangyang¹^ORCID,Pu Jian²^ORCID

Affiliation:

1. Shanghai Key Lab of Intelligent Information Processing and the School of Computer Science, Fudan University, Shanghai, China

2. Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China

Funder

NSFC Project

Shanghai Municipal Science and Technology Major Project

ZJLab, Shanghai Center for Brain Science and Brain-Inspired Technology

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7274857/10510053/10379107.pdf?arnumber=10379107

Reference65 articles.

1. PolarMix: A general data augmentation technique for LiDAR point clouds;Xiao,2022

2. SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences

3. Incorporating Human Domain Knowledge in 3-D LiDAR-Based Semantic Segmentation

4. Multi-to-Single Knowledge Distillation for Point Cloud Semantic Segmentation

5. Lidar Mapping Optimization Based on Lightweight Semantic Segmentation

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