The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.
Structured3D: A Large Photo-Realistic Dataset for Structured 3D Modeling
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Cites
Indoor segmentation and support inference from rgbd images
Silberman, N., Hoiem, D., Kohli, P., & Fergus, R. (2012) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-33715-4_54 · Cited by 5,760
ScanNet: Richly-Annotated 3D Reconstructions of Indoor Scenes
Dai, A., Chang, A. X., Savva, M., Halber, M., Funkhouser, T., & Niessner, M. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.261 · Cited by 4,368
Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age
Cadena, C., Carlone, L., Carrillo, H., Latif, Y., Scaramuzza, D., Neira, J., Reid, I., & Leonard, J. J. (2016) · IEEE Transactions on Robotics · doi:10.1109/tro.2016.2624754 · Cited by 3,596
Past, present, and future of simultaneous localization and mapping: Toward the robust-perception age
Cadena, C., Carlone, L., Carrillo, H., Latif, Y., Scaramuzza, D., Neira, J., Reid, I. D., & Leonard, J. J. (2016) · Zurich Open Repository and Archive (University of Zurich) · doi:10.5167/uzh-138892 · Cited by 3,048
SUN RGB-D: A RGB-D scene understanding benchmark suite
Song, S., Lichtenberg, S. P., & Xiao, J. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298655 · Cited by 1,943
3D Semantic Parsing of Large-Scale Indoor Spaces
Armeni, I., Sener, O., Zamir, A. R., Jiang, H., Brilakis, I., Fischer, M., & Savarese, S. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.170 · Cited by 1,892
Matterport3D: Learning from RGB-D Data in Indoor Environments
Chang, A., Dai, A., Funkhouser, T., Halber, M., Niebner, M., Savva, M., Song, S., Zeng, A., & Zhang, Y. (2017) · 2017 International Conference on 3D Vision (3DV) · doi:10.1109/3dv.2017.00081 · Cited by 1,858
Learning to Adapt Structured Output Space for Semantic Segmentation
Tsai, Y.-H., Hung, W.-C., Schulter, S., Sohn, K., Yang, M.-H., & Chandraker, M. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00780 · Cited by 1,430
Semantic Scene Completion from a Single Depth Image
Song, S., Yu, F., Zeng, A., Chang, A. X., Savva, M., & Funkhouser, T. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.28 · Cited by 1,209
A Papier-Mache Approach to Learning 3D Surface Generation
Groueix, T., Fisher, M., Kim, V. G., Russell, B. C., & Aubry, M. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00030 · Cited by 910
Cited by
Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understanding
Roberts, M., Ramapuram, J., Ranjan, A., Kumar, A., Bautista, M. A., Paczan, N., Webb, R., & Susskind, J. M. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.01073 · Cited by 358
Metadata
- Authors
- Zheng, J., Zhang, J., Li, J., Tang, R., Gao, S., & Zhou, Z.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2020
- Pages
- 519-535
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W3109728105
- Cited by
- 282
- References
- 42
- FWCI
- 29.70
- Type
- conference paper
- Language
- en
- Open access
- green
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- CoChat. (2026). Citation check: Structured3D: A Large Photo-Realistic Dataset for Structured 3D Modeling. https://app.cochat.ai/papers/10.1007/978-3-030-58545-7_30
- The paper
- Zheng, J., Zhang, J., Li, J., Tang, R., Gao, S., & Zhou, Z. (2020). Structured3D: A Large Photo-Realistic Dataset for Structured 3D Modeling. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-030-58545-7_30
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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.
