The DOI matches its Crossref record; 60 of the 60 references it cites were found in a registry or an index.
Deep Local Shapes: Learning Local SDF Priors for Detailed 3D Reconstruction
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Cites
Multilayer feedforward networks are universal approximators
Hornik, K., Stinchcombe, M., & White, H. (1989) · Neural Networks · doi:10.1016/0893-6080(89)90020-8 · Cited by 21,728
Multilayer feedforward networks are universal approximators
HornikK., StinchcombeM., & WhiteH. (1989) · Neural Networks · doi:10.5555/70405.70408 · Cited by 9,081
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
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
Parallel Tracking and Mapping for Small AR Workspaces
Klein, G., & Murray, D. (2007) · 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality · doi:10.1109/ismar.2007.4538852 · Cited by 4,346
KinectFusion: Real-time dense surface mapping and tracking
Newcombe, R. A., Fitzgibbon, A., Izadi, S., Hilliges, O., Molyneaux, D., Kim, D., Davison, A. J., Kohi, P., Shotton, J., & Hodges, S. (2011) · 2011 10th IEEE International Symposium on Mixed and Augmented Reality · doi:10.1109/ismar.2011.6092378 · Cited by 4,008
Self-citationDeepSDF: Learning Continuous Signed Distance Functions for Shape Representation
Park, J. J., Florence, P., Straub, J., Newcombe, R., & Lovegrove, S. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00025 · Cited by 3,422
Self-citationORB-SLAM: A Versatile and Accurate Monocular SLAM System
Mur-Artal, R., Montiel, J. M. M., & Tardos, J. D. (2015) · Zaguan (Universidad de Zaragoza) · Cited by 3,153
A volumetric method for building complex models from range images
Curless, B., & Levoy, M. (1996) · Proceedings of the 23rd annual conference on Computer graphics and interactive techniques · doi:10.1145/237170.237269 · Cited by 3,124
Engel, J., Koltun, V., & Cremers, D. (2018) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2017.2658577 · Cited by 2,924
Cited by
pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis
Chan, E. R., Monteiro, M., Kellnhofer, P., Wu, J., & Wetzstein, G. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr46437.2021.00574 · Cited by 689
UniSim: A Neural Closed-Loop Sensor Simulator
Yang, Z., Chen, Y., Wang, J., Manivasagam, S., Ma, W.-C., Yang, A. J., & Urtasun, R. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52729.2023.00140 · Cited by 170
Metadata
- Authors
- Chabra, R., Lenssen, J. E., Ilg, E., Schmidt, T., Straub, J., Lovegrove, S., & Newcombe, R.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2020
- Pages
- 608-625
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W3013987637
- Cited by
- 380
- References
- 60
- FWCI
- 53.41
- Type
- conference paper
- Language
- en
- Open access
- green
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- CoChat. (2026). Citation check: Deep Local Shapes: Learning Local SDF Priors for Detailed 3D Reconstruction. https://app.cochat.ai/papers/10.1007/978-3-030-58526-6_36
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- Chabra, R., Lenssen, J. E., Ilg, E., Schmidt, T., Straub, J., Lovegrove, S., & Newcombe, R. (2020). Deep Local Shapes: Learning Local SDF Priors for Detailed 3D Reconstruction. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-030-58526-6_36
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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.
