Fast simplification with sharp feature preserving for 3D point clouds-Reference-Cited by-同舟云学术

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Fast simplification with sharp feature preserving for 3D point clouds

Published:2013-04 Issue: Volume: Page:
ISSN:
Container-title:2013 11th International Symposium on Programming and Systems (ISPS)
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Author:

Benhabiles Halim,Aubreton Olivier,Barki Hichem,Tabia Hedi

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/6578009/6581470/06581492.pdf?arnumber=6581492

Cited by 26 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. Task-Driven Learning Downsampling Network Based Phase-Resolved Wave Fields Reconstruction with Remote Optical Observations;Journal of Marine Science and Engineering;2024-06-27

2. Learnable Skeleton-Aware 3D Point Cloud Sampling;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR);2023-06

3. Point Density Variations in Airborne Lidar Point Clouds;Sensors;2023-02-01

4. A Framework of Point Cloud Simplification Based on Voxel Grid and Its Applications;IEEE Sensors Journal;2023

5. Point Cloud Sampling via Graph Balancing and Gershgorin Disc Alignment;IEEE Transactions on Pattern Analysis and Machine Intelligence;2023-01-01

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