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Normal estimation for unstructured point clouds is an important task in 3D computer vision.
A note on a method for generating points uniformly on n-dimensional spheres
Muller, M. E. (1959) · 1959
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Surface reconstruction from unorganized points
Hoppe, H., DeRose, T., Duchamp, T., McDonald, J., and Stuetzle, W. (1992) · 1992
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The approximation power of moving least-squares
Levin, D. (1998) · 1998
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Surface reconstruction by voronoi filtering
Amenta et al. (1999) · 1999
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Estimating differential quantities using polynomial fitting of osculating jets
Cazals, F. and Pouget, M. (2005) · 2005
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Poisson surface reconstruction
Kazhdan, M., Bolitho, M., and Hoppe, H. (2006) · 2006
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Voronoi-based curvature and feature estimation from point clouds
Mérigot et al. (2010) · 2010
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Signing the unsigned: Robust surface reconstruction from raw pointsets
Mullen, P., De Goes, F., Desbrun, M., Cohen-Steiner, D., and Alliez, P. (2010) · 2010
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A review of point cloud registration algorithms for mobile robotics
Pomerleau, F., Colas, F., Siegwart, R., et al. (2015) · 2015
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Deep points consolidation
Wu, S., Huang, H., Gong, M., Zwicker, M., and Cohen-Or, D. (2015) · 2015
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Deep learning for robust normal estimation in unstructured point clouds
Boulch, A. et al. (2016) · 2016
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Scenenn: A scene meshes dataset with annotations
Hua, B.-S., Pham, Q.-H., Nguyen, D. T., Tran, M.-K., Yu, L.-F., and Yeung, S.-K. (2016) · 2016
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Visibility-consistent thin surface reconstruction using multi-scale kernels
Aroudj, S., Seemann, P., Langguth, F., Guthe, S., and Goesele, M. (2017) · 2017
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A review of point clouds segmentation and classification algorithms
Grilli, E., Menna, F., and Remondino, F. (2017) · 2017
Cited alongside, same era.
SEMANTIC3D.NET: A new large-scale point cloud classification benchmark
Hackel, T., Savinov, N., Ladicky, L., Wegner, J. D., Schindler, K., and Pollefeys, M. (2017) · 2017
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PointNet: Deep learning on point sets for 3d classification and segmentation
Qi, C. R. et al. (2017) · 2017
Cited alongside, same era.
PCPNet: Learning local shape properties from raw point clouds
Guerrero, P. et al. (2018) · 2018
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Nesti-net: Normal estimation for unstructured 3d point clouds using convolutional neural networks
DeepFit: 3d surface fitting via neural network weighted least squares
Ben-Shabat, Y. et al. (2020) · 2020
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Deep iterative surface normal estimation
Lenssen, J. E. et al. (2020) · 2020
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NeRF: Representing scenes as neural radiance fields for view synthesis
Mildenhall, B., Srinivasan, P. P., Tancik, M., Barron, J. T., Ramamoorthi, R., and Ng, R. (2020) · 2020
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Point cloud normal estimation with graph-convolutional neural networks
Pistilli, F., Fracastoro, G., Valsesia, D., and Magli, E. (2020) · 2020
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Neighbourhood-insensitive point cloud normal estimation network
Wang, Z. et al. (2020) · 2020
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Normal estimation for 3d point clouds via local plane constraint and multi-scale selection
Zhou, J. et al. (2020) · 2020
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Ben-Shabat, Y. et al. (2019) · 2019
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Learning implicit fields for generative shape modeling
Chen, Z. and Zhang, H. (2019) · 2019
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Normal estimation for accurate 3d mesh reconstruction with point cloud model incorporating spatial structure
Hashimoto, T. and Saito, M. (2019) · 2019
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Learning transformation synchronization
Huang, X., Liang, Z., Zhou, X., Xie, Y., Guibas, L. J., and Huang, Q. (2019) · 2019
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Occupancy networks: Learning 3d reconstruction in function space
Mescheder, L., Oechsle, M., Niemeyer, M., Nowozin, S., and Geiger, A. (2019) · 2019
Cited alongside, same era.
Implicit surface representations as layers in neural networks
Michalkiewicz, M., Pontes, J. K., Jack, D., Baktashmotlagh, M., and Eriksson, A. (2019) · 2019
Cited alongside, same era.
DeepSDF: Learning continuous signed distance functions for shape representation
Park, J. J., Florence, P., Straub, J., Newcombe, R., and Lovegrove, S. (2019) · 2019
Cited alongside, same era.
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Latent tangent space representation for normal estimation
Cao, J., Zhu, H., Bai, Y., Zhou, J., Pan, J., and Su, Z. (2021) · 2021
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Orienting point clouds with dipole propagation
Metzer, G., Hanocka, R., Zorin, D., Giryes, R., Panozzo, D., and Cohen-Or, D. (2021) · 2021
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Improvement of normal estimation for pointclouds via simplifying surface fitting
Zhou, J., Jin, W., Wang, M., Liu, X., Li, Z., and Liu, Z. (2021) · 2021
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Adafit: Rethinking learning-based normal estimation on point clouds
Zhu, R., Liu, Y., Dong, Z., Wang, Y., Jiang, T., Wang, W., and Yang, B. (2021) · 2021
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Latent partition implicit with surface codes for 3d representation
Chen, C., Liu, Y.-S., and Han, Z. (2022) · 2022
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Geometry guided deep surface normal estimation
Zhang, J., Cao, J.-J., Zhu, H.-R., Yan, D.-M., and Liu, X.-P. (2022) · 2022
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