The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
PPF-FoldNet: Unsupervised Learning of Rotation Invariant 3D Local Descriptors
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Deep Residual Learning for Image Recognition
He, K., Zhang, X., Ren, S., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.90 · Cited by 235,474
ImageNet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155
Adam: A Method for Stochastic Optimization
Kingma, D. P., & Ba, J. (2014) · arXiv · doi:10.48550/arxiv.1412.6980 · Cited by 98,946
Object recognition from local scale-invariant features
Lowe, D. G. (1999) · Proceedings of the Seventh IEEE International Conference on Computer Vision · doi:10.1109/iccv.1999.790410 · Cited by 16,472
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., Corrado, G. S., Davis, A., Dean, J., Devin, M., et al. (2016) · arXiv · doi:10.48550/arxiv.1603.04467 · Cited by 9,408
Dynamic Graph CNN for Learning on Point Clouds
Wang, Y., Sun, Y., Liu, Z., Sarma, S. E., Bronstein, M. M., & Solomon, J. M. (2019) · ACM Transactions on Graphics · doi:10.1145/3326362 · Cited by 7,199
ORB-SLAM: A Versatile and Accurate Monocular SLAM System
Mur-Artal, R., Montiel, J. M. M., & Tardos, J. D. (2015) · IEEE Transactions on Robotics · doi:10.1109/tro.2015.2463671 · Cited by 6,778
Frustum PointNets for 3D Object Detection from RGB-D Data
Qi, C. R., Liu, W., Wu, C., Su, H., & Guibas, L. J. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00102 · Cited by 2,655
3D Graph Neural Networks for RGBD Semantic Segmentation
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Unsupervised feature learning for 3D scene labeling
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Cited by
Deep Closest Point: Learning Representations for Point Cloud Registration
Wang, Y., & Solomon, J. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00362 · Cited by 1,112
Fully Convolutional Geometric Features
Choy, C., Park, J., & Koltun, V. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00905 · Cited by 759
PREDATOR: Registration of 3D Point Clouds with Low Overlap
Huang, S., Gojcic, Z., Usvyatsov, M., Wieser, A., & Schindler, K. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr46437.2021.00425 · Cited by 721
Registration of large-scale terrestrial laser scanner point clouds: A review and benchmark
Dong, Z., Liang, F., Yang, B., Xu, Y., Zang, Y., Li, J., Wang, Y., Dai, W., Fan, H., Hyyppä, J., et al. (2020) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2020.03.013 · Cited by 438
Patch-Based Progressive 3D Point Set Upsampling
Yifan, W., Wu, S., Huang, H., Cohen-Or, D., & Sorkine-Hornung, O. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00611 · Cited by 317
Metadata
- Authors
- Deng, H., Birdal, T., & Ilic, S.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2018
- Pages
- 620-638
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2889300857
- Cited by
- 400
- References
- 10
- FWCI
- 57.66
- Type
- conference paper
- Language
- en
- Open access
- green
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- CoChat. (2026). Citation check: PPF-FoldNet: Unsupervised Learning of Rotation Invariant 3D Local Descriptors. https://app.cochat.ai/papers/10.1007/978-3-030-01228-1_37
- The paper
- Deng, H., Birdal, T., & Ilic, S. (2018). PPF-FoldNet: Unsupervised Learning of Rotation Invariant 3D Local Descriptors. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-030-01228-1_37
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
