The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
SuperGlue: Learning Feature Matching With Graph Neural Networks
Open accessAbstract
This paper introduces SuperGlue, a neural network that matches two sets of local features by jointly finding correspondences and rejecting non-matchable points. Assignments are estimated by solving a differentiable optimal transport problem, whose costs are predicted by a graph neural network. We introduce a flexible context aggregation mechanism based on attention, enabling SuperGlue to reason about the underlying 3D scene and feature assignments jointly. Compared to traditional, hand-designed heuristics, our technique learns priors over geometric transformations and regularities of the 3D world through end-to-end training from image pairs. SuperGlue outperforms other learned approaches and achieves state-of-the-art results on the task of pose estimation in challenging real-world indoor and outdoor environments. The proposed method performs matching in real-time on a modern GPU and can be readily integrated into modern SfM or SLAM systems. The code and trained weights are publicly available at github.com/magicleap/SuperGluePretrainedNetwork.
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Structure-from-Motion Revisited
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Bai, X., Hu, Z., Zhu, X., Huang, Q., Chen, Y., Fu, H., & Tai, C.-L. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52688.2022.00116 · Cited by 990
Image Matching from Handcrafted to Deep Features: A Survey
Ma, J., Jiang, X., Fan, A., Jiang, J., & Yan, J. (2021) · International Journal of Computer Vision · doi:10.1007/s11263-020-01359-2 · Cited by 990
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
Metadata
- Authors
- Sarlin, P.-E., DeTone, D., Malisiewicz, T., & Rabinovich, A.
- Venue
- 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
- Publisher
- IEEE
- Published
- 2020-06
- Pages
- 4937-4946
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2990957769
- Cited by
- 2,830
- References
- 12
- FWCI
- 90.51
- Type
- conference paper
- Language
- en
- Open access
- green
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- Sarlin, P.-E., DeTone, D., Malisiewicz, T., & Rabinovich, A. (2020). SuperGlue: Learning Feature Matching With Graph Neural Networks. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). https://doi.org/10.1109/cvpr42600.2020.00499
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