The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Using Multiple Hypotheses to Improve Depth-Maps for Multi-View Stereo
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Citations
Cites
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
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
Evaluation of Stereo Matching Costs on Images with Radiometric Differences
Hirschmuller, H., & Scharstein, D. (2009) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2008.221 · Cited by 721
High-quality streamable free-viewpoint video
Collet, A., Chuang, M., Sweeney, P., Gillett, D., Evseev, D., Calabrese, D., Hoppe, H., Kirk, A., & Sullivan, S. (2015) · ACM Transactions on Graphics · doi:10.1145/2766945 · Cited by 573
PatchmatchNet: Learned Multi-View Patchmatch Stereo
Wang, F., Galliani, S., Vogel, C., Speciale, P., & Pollefeys, M. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr46437.2021.01397 · Cited by 420
Metadata
- Authors
- Campbell, N. D. F., Vogiatzis, G., Hernández, C., & Cipolla, R.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2008
- Pages
- 766-779
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W1539230104
- Cited by
- 390
- References
- 1
- FWCI
- 10.42
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Using Multiple Hypotheses to Improve Depth-Maps for Multi-View Stereo. https://app.cochat.ai/papers/10.1007/978-3-540-88682-2_58
- The paper
- Campbell, N. D. F., Vogiatzis, G., Hernández, C., & Cipolla, R. (2008). Using Multiple Hypotheses to Improve Depth-Maps for Multi-View Stereo. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-540-88682-2_58
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.
