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Point Signatures: A New Representation for 3D Object Recognition
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Citations
Cited by
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
Zhou, Y., & Tuzel, O. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00472 · Cited by 4,813
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
Unique Signatures of Histograms for Local Surface Description
Tombari, F., Salti, S., & Di Stefano, L. (2010) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-15558-1_26 · Cited by 1,480
A Concise and Provably Informative Multi‐Scale Signature Based on Heat Diffusion
Sun, J., Ovsjanikov, M., & Guibas, L. (2009) · Computer Graphics Forum · doi:10.1111/j.1467-8659.2009.01515.x · Cited by 1,450
SHOT: Unique signatures of histograms for surface and texture description
Salti, S., Tombari, F., & Di Stefano, L. (2014) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2014.04.011 · Cited by 987
Metadata
- Authors
- Chua, C. S., & Jarvis, R.
- Venue
- International Journal of Computer Vision
- Published
- 1997-10
- Volume
- 25
- Issue
- 1
- Pages
- 63-85
- ISSN
- 0920-5691 (ISSN-L)
- 1573-1405
- OpenAlex
- W1563354748
- Cited by
- 587
- References
- 0
- FWCI
- 3.89
- Type
- journal article
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
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- CoChat. (2026). Citation check: Point Signatures: A New Representation for 3D Object Recognition. https://app.cochat.ai/papers/10.1023/a:1007981719186
- The paper
- Chua, C. S., & Jarvis, R. (1997). Point Signatures: A New Representation for 3D Object Recognition. International Journal of Computer Vision. https://doi.org/10.1023/a%3A1007981719186
Data sources
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.