The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Efficient large-scale multi-view stereo for ultra high-resolution image sets
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Citations
Cites
Distinctive Image Features from Scale-Invariant Keypoints
Lowe, D. G. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000029664.99615.94 · Cited by 55,589
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
A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms
Seitz, S. M., Curless, B., Diebel, J., Scharstein, D., & Szeliski, R. (2006) · 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (CVPR'06) · doi:10.1109/cvpr.2006.19 · Cited by 2,457
Cited by
MVSNet: Depth Inference for Unstructured Multi-view Stereo
Yao, Y., Luo, Z., Li, S., Fang, T., & Quan, L. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-01237-3_47 · Cited by 1,455
Multi-view learning overview: Recent progress and new challenges
Zhao, J., Xie, X., Xu, X., & Sun, S. (2017) · Information Fusion · doi:10.1016/j.inffus.2017.02.007 · Cited by 1,002
Differentiable Volumetric Rendering: Learning Implicit 3D Representations Without 3D Supervision
Niemeyer, M., Mescheder, L., Oechsle, M., & Geiger, A. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00356 · Cited by 834
Large Scale Multi-view Stereopsis Evaluation
Jensen, R., Dahl, A., Vogiatzis, G., Tola, E., & Aanaes, H. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2014.59 · Cited by 729
Self-citationRecurrent MVSNet for High-Resolution Multi-View Stereo Depth Inference
Yao, Y., Luo, Z., Li, S., Shen, T., Fang, T., & Quan, L. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00567 · Cited by 666
Metadata
- Authors
- Tola, E., Strecha, C., & Fua, P.
- Venue
- Machine Vision and Applications
- Published
- 2011-05-28
- Volume
- 23
- Issue
- 5
- Pages
- 903-920
- ISSN
- 0932-8092 (ISSN-L)
- 1432-1769
- OpenAlex
- W2128052895
- Cited by
- 328
- References
- 3
- FWCI
- 8.28
- Type
- journal article
- Language
- en
- Open access
- green
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- CoChat. (2026). Citation check: Efficient large-scale multi-view stereo for ultra high-resolution image sets. https://app.cochat.ai/papers/10.1007/s00138-011-0346-8
- The paper
- Tola, E., Strecha, C., & Fua, P. (2012). Efficient large-scale multi-view stereo for ultra high-resolution image sets. Machine Vision and Applications. https://doi.org/10.1007/s00138-011-0346-8
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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.
