Robust point cloud normal estimation via multi-level critical point aggregation-Reference-Cited by-同舟云学术

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Robust point cloud normal estimation via multi-level critical point aggregation

Published:2024-06-21 Issue: Volume: Page:
ISSN:0178-2789
Container-title:The Visual Computer
language:en
Short-container-title:Vis Comput

Author:

Zhou Jun,Li Yaoshun,Wang Mingjie,Li Nannan,Li Zhiyang,Wang Weixiao

Funder

Natural Science Foundation of China

China Postdoctoral Science Foundation

Science Foundation of Zhejiang Sci-Tech University

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s00371-024-03532-x.pdf

Reference33 articles.

1. Zhu, R., Liu, Y., Dong, Z., Wang, Y., Jiang, T., Wang, W., Yang, B.: Adafit: rethinking learning-based normal estimation on point clouds. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 6118–6127 (2021)

2. Hoppe, H., DeRose, T., Duchamp, T., McDonald, J., Stuetzle, W.: Surface reconstruction from unorganized points. In: Proceedings of the 19th Annual Conference on Computer Graphics and Interactive Techniques, pp. 71–78 (1992)

3. Stewart, G.W.: On the early history of the singular value decomposition. SIAM Rev. 35(4), 551–566 (1993)

4. Guerrero, P., Kleiman, Y., Ovsjanikov, M., Mitra, N.J.: Pcpnet learning local shape properties from raw point clouds. In: Computer Graphics Forum, vol. 37, pp. 75–85 (2018). Wiley Online Library

5. Ben-Shabat, Y., Lindenbaum, M., Fischer, A.: Nesti-net: normal estimation for unstructured 3D point clouds using convolutional neural networks. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 10112–10120 (2019)

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