The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.
Learning SO(3) Equivariant Representations with Spherical CNNs
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ImageNet Large Scale Visual Recognition Challenge
Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., et al. (2015) · International Journal of Computer Vision · doi:10.1007/s11263-015-0816-y · Cited by 39,380
FaceNet: A unified embedding for face recognition and clustering
Schroff, F., Kalenichenko, D., & Philbin, J. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298682 · Cited by 15,267
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
Charles, R. Q., Su, H., Kaichun, M., & Guibas, L. J. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.16 · Cited by 9,237
Gorski, K. M., Hivon, E., Banday, A. J., Wandelt, B. D., Hansen, F. K., Reinecke, M., & Bartelmann, M. (2005) · The Astrophysical Journal · doi:10.1086/427976 · Cited by 5,958
3D ShapeNets: A deep representation for volumetric shapes
Wu, Z., Song, S., Khosla, A., Yu, F., Zhang, L., Tang, X., & Xiao, J. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298801 · Cited by 4,550
Spectral Networks and Locally Connected Networks on Graphs
Bruna, J., Zaremba, W., Szlam, A., & LeCun, Y. (2013) · arXiv · doi:10.48550/arxiv.1312.6203 · Cited by 3,983
Geometric Deep Learning: Going beyond Euclidean data
Bronstein, M. M., Bruna, J., LeCun, Y., Szlam, A., & Vandergheynst, P. (2017) · IEEE Signal Processing Magazine · doi:10.1109/msp.2017.2693418 · Cited by 3,661
Multi-view Convolutional Neural Networks for 3D Shape Recognition
Su, H., Maji, S., Kalogerakis, E., & Learned-Miller, E. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.114 · Cited by 3,480
VoxNet: A 3D Convolutional Neural Network for real-time object recognition
Maturana, D., & Scherer, S. (2015) · 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2015.7353481 · Cited by 3,458
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
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Cited by
Perceiver: General Perception with Iterative Attention
Jaegle, A., Gimeno, F., Brock, A., Zisserman, A., Vinyals, O., & Carreira, J. (2021) · arXiv · doi:10.48550/arxiv.2103.03206 · Cited by 414
3DRegNet: A Deep Neural Network for 3D Point Registration
Pais, G. D., Ramalingam, S., Govindu, V. M., Nascimento, J. C., Chellappa, R., & Miraldo, P. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00722 · Cited by 268
Perraudin, N., Defferrard, M., Kacprzak, T., & Sgier, R. (2019) · Astronomy and Computing · doi:10.1016/j.ascom.2019.03.004 · Cited by 184
3D AffordanceNet: A Benchmark for Visual Object Affordance Understanding
Deng, S., Xu, X., Wu, C., Chen, K., & Jia, K. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr46437.2021.00182 · Cited by 124
Nonlinear 3D cosmic web simulation with heavy-tailed generative adversarial networks
Feder, R. M., Berger, P., & Stein, G. (2020) · Physical Review D · doi:10.1103/physrevd.102.103504 · Cited by 30
Metadata
- Authors
- Esteves, C., Allen-Blanchette, C., Makadia, A., & Daniilidis, K.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2018
- Pages
- 54-70
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2796422723
- Cited by
- 373
- References
- 37
- FWCI
- 69.49
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Esteves, C., Allen-Blanchette, C., Makadia, A., & Daniilidis, K. (2018). Learning SO(3) Equivariant Representations with Spherical CNNs. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-030-01261-8_4
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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.
