PFRNet: 3-D partial-to-full point cloud registration network for arbitrary pose matching
Author:
Funder
Ministry of Science and Technology, Taiwan
Publisher
Springer Science and Business Media LLC
Subject
Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Software
Link
https://link.springer.com/content/pdf/10.1007/s00371-023-03209-x.pdf
Reference65 articles.
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3. Armeni, I., Sener, O., Zamir, A.R., Jiang, H., Brilakis, I., Fischer, M., Savarese, S.: 3D semantic parsing of large-scale indoor spaces. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1534–1543 (2016)
4. Basdogan, C., Oztireli, A.C.: A new feature-based method for robust and efficient rigid-body registration of overlapping point clouds. Vis. Comput. 24(7–9), 679–688 (2008)
5. Ben-Shabat, Y., Gould, S.: DeepFit: 3D surface fitting via neural network weighted least squares. In: Computer Vision—ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part I 16, pp. 20–34. Springer (2020)
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