A Large-Scale Network Construction and Lightweighting Method for Point Cloud Semantic Segmentation-Reference-Cited by-同舟云学术

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A Large-Scale Network Construction and Lightweighting Method for Point Cloud Semantic Segmentation

Published:2024 Issue: Volume:33 Page:2004-2017
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Han Jiawei¹^ORCID,Liu Kaiqi¹^ORCID,Li Wei¹^ORCID,Chen Guangzhi²^ORCID,Wang Wenguang³^ORCID,Zhang Feng¹^ORCID

Affiliation:

1. School of Information and Electronics, Beijing Institute of Technology, Beijing Key Laboratory of Fractional Signals and Systems, Beijing, China

2. Research Institute for Frontier Science, Beihang University, Beijing, China

3. School of Electronic Information Engineering, Beihang University, Beijing, China

Funder

National Natural Science Foundation of China

State Key Laboratory of Intelligent Green Vehicle and Mobility

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/83/10346232/10462927.pdf?arnumber=10462927

Reference54 articles.

1. PointNet: Deep learning on point sets for 3D classification and segmentation;Qi

2. PointNet++: Deep hierarchical feature learning on point sets in a metric space;Qi

3. Large-Scale Point Cloud Semantic Segmentation with Superpoint Graphs

4. RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds

5. Semantic Segmentation for Real Point Cloud Scenes via Bilateral Augmentation and Adaptive Fusion

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. RAAFNet: Reverse Attention Adaptive Fusion Network for Large-Scale Point Cloud Semantic Segmentation;Mathematics;2024-08-12

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