The DOI matches its Crossref record; 31 of the 33 references it cites were found in a registry or an index.
Automatic photo pop-up
Abstract
This paper presents a fully automatic method for creating a 3D model from a single photograph. The model is made up of several texture-mapped planar billboards and has the complexity of a typical children's pop-up book illustration. Our main insight is that instead of attempting to recover precise geometry, we statistically model geometric classes defined by their orientations in the scene. Our algorithm labels regions of the input image into coarse categories: "ground", "sky", and "vertical". These labels are then used to "cut and fold" the image into a pop-up model using a set of simple assumptions. Because of the inherent ambiguity of the problem and the statistical nature of the approach, the algorithm is not expected to work on every image. However. it performs surprisingly well for a wide range of scenes taken from a typical person's photo album.
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“As a baseline we compare against the pose network used by [62], which builds upon [76] with an additional scaling of the translation by the mean of the inverse depth.”
From Digging Into Self-Supervised Monocular Depth Estimation (2019) · cites this paper as [62]
Citations
Cites
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Hartley, R., & Zisserman, A. (2004) · doi:10.1017/cbo9780511811685 · Cited by 21,070
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Use of the hough transformation to detect lines and curves in pictures
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Efficient Graph-Based Image Segmentation
Felzenszwalb, P. F., & Huttenlocher, D. P. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000022288.19776.77 · Cited by 6,205
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Hartley, R. I., & Zisserman, A. (2003) · Cambridge University Press eBooks · Cited by 2,747
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Research works printed but not linked: 1
- 10.5555/839287.1515131 · DOI
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Items 601–608 of 608
Single-image autostereoscopic 3D display via depth-adaptive integral imaging
Zhang, Y., Wang, H., Li, H., Du, Y., Fu, Y., Shen, Y., Lin, W.-X., & Zheng, X. (2025) · Optics Communications · doi:10.1016/j.optcom.2025.132598
On the relevance of patch-based extraction methods for monocular depth estimation
Coscia, P., Fusillo, A., Genovese, A., Piuri, V., & Scotti, F. (2025) · Image and Vision Computing · doi:10.1016/j.imavis.2025.105857
Cai, X., Wang, Y., Fan, Z., Deng, H., Wang, S., Li, W., Li, D., Luo, L., Wang, M., Zhang, H., et al. (2026) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2026.3677463
Perception Module of Autonomous Driving
Huang, Y., & Yang, Z. (2026) · Springer eBooks · doi:10.1007/978-981-95-3725-9_5
FuseDPT: Multi-scale and Multi-projection Model for Learning Depth in 360$$^\circ $$C
Paula, M. D. O. P., İmamoğlu, N., Caron, G., & André, A. N. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-31666-0_23
Depth Map Prediction from a Single Image using a Multi-Scale Deep Network
Eigen, D., Puhrsch, C., & Fergus, R. (2014) · arXiv · doi:10.48550/arxiv.1406.2283 · Cited by 3,442
Unsupervised Monocular Depth Estimation with Left-Right Consistency
Godard, C., Mac Aodha, O., & Brostow, G. J. (2016) · arXiv · doi:10.48550/arxiv.1609.03677 · Cited by 28
Metadata
- Authors
- Hoiem, D., Efros, A. A., & Hebert, M.
- Affiliations
- Carnegie Mellon University (US)
- Venue
- ACM Transactions on Graphics
- Published
- 2005-07
- Volume
- 24
- Issue
- 3
- Pages
- 577-584
- ISSN
- 0730-0301 (ISSN-L)
- 1557-7368
- OpenAlex
- W2151996626
- Cited by
- 616
- References
- 33
- Citations by year
- 2026: 3 · 2025: 9 · 2024: 7 · 2023: 7 · 2022: 23 · 2021: 25 · 2020: 30 · 2019: 48 · 2018: 59 · 2017: 33 · 2016: 43 · 2015: 38 · 2014: 39 · 2013: 36 · 2012: 33
- FWCI
- 24.16
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- ACM Transactions on Graphics (publishedVersion)
- KiltHub Repository (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › 3D Shape Modeling and Analysis
- Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Computer Graphics and Visualization Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Keywords
- automatic 3D model generation, single-image 3D reconstruction, image segmentation
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