The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Efficient Large-Scale Stereo Matching
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Citations
Cites
SURF: Speeded Up Robust Features
Bay, H., Tuytelaars, T., & Van Gool, L. (2006) · Lecture Notes in Computer Science · doi:10.1007/11744023_32 · Cited by 14,955
Triangle: Engineering a 2D quality mesh generator and Delaunay triangulator
Shewchuk, J. R. (1996) · Lecture Notes in Computer Science · doi:10.1007/bfb0014497 · Cited by 2,115
Cited by
Are we ready for autonomous driving? The KITTI vision benchmark suite
Geiger, A., Lenz, P., & Urtasun, R. (2012) · 2012 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2012.6248074 · Cited by 14,897
Self-citationHigh-Resolution Stereo Datasets with Subpixel-Accurate Ground Truth
Scharstein, D., Hirschmüller, H., Kitajima, Y., Krathwohl, G., Nešić, N., Wang, X., & Westling, P. (2014) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-11752-2_3 · Cited by 1,305
A Multi-view Stereo Benchmark with High-Resolution Images and Multi-camera Videos
Schops, T., Schonberger, J. L., Galliani, S., Sattler, T., Schindler, K., Pollefeys, M., & Geiger, A. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.272 · Cited by 915
Self-citationIntel(R) RealSense(TM) Stereoscopic Depth Cameras
Keselman, L., Woodfill, J. I., Grunnet-Jepsen, A., & Bhowmik, A. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2017.167 · Cited by 448
Zhu, Z., Ng, D. W. H., Park, H. S., & McAlpine, M. C. (2020) · Nature Reviews Materials · doi:10.1038/s41578-020-00235-2 · Cited by 348
Metadata
- Authors
- Geiger, A., Roser, M., & Urtasun, R.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2011
- Pages
- 25-38
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W1912649600
- Cited by
- 761
- References
- 2
- FWCI
- 38.26
- Type
- conference paper
- 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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- CoChat. (2026). Citation check: Efficient Large-Scale Stereo Matching. https://app.cochat.ai/papers/10.1007/978-3-642-19315-6_3
- The paper
- Geiger, A., Roser, M., & Urtasun, R. (2011). Efficient Large-Scale Stereo Matching. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-642-19315-6_3
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.
