The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Fully-Convolutional Point Networks for Large-Scale Point Clouds
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Cites
V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation
Milletari, F., Navab, N., & Ahmadi, S.-A. (2016) · 2016 Fourth International Conference on 3D Vision (3DV) · doi:10.1109/3dv.2016.79 · Cited by 11,931
Self-citation3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation
Çiçek, Ö., Abdulkadir, A., Lienkamp, S. S., Brox, T., & Ronneberger, O. (2016) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-46723-8_49 · Cited by 7,945
SyncSpecCNN: Synchronized Spectral CNN for 3D Shape Segmentation
Yi, L., Su, H., Guo, X., & Guibas, L. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.697 · Cited by 461
Cited by
KPConv: Flexible and Deformable Convolution for Point Clouds
Thomas, H., Qi, C. R., Deschaud, J.-E., Marcotegui, B., Goulette, F., & Guibas, L. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00651 · Cited by 3,212
SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences
Behley, J., Garbade, M., Milioto, A., Quenzel, J., Behnke, S., Stachniss, C., & Gall, J. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00939 · Cited by 2,294
RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds
Hu, Q., Yang, B., Xie, L., Rosa, S., Guo, Y., Wang, Z., Trigoni, N., & Markham, A. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.01112 · Cited by 2,275
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
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
- Rethage, D., Wald, J., Sturm, J., Navab, N., & Tombari, F.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2018
- Pages
- 625-640
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2888754481
- Cited by
- 203
- References
- 3
- FWCI
- 34.37
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Fully-Convolutional Point Networks for Large-Scale Point Clouds. https://app.cochat.ai/papers/10.1007/978-3-030-01225-0_37
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- Rethage, D., Wald, J., Sturm, J., Navab, N., & Tombari, F. (2018). Fully-Convolutional Point Networks for Large-Scale Point Clouds. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-030-01225-0_37
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
