The DOI matches its Crossref record; 32 of the 35 references it cites were found in a registry or an index.
Recovering Occlusion Boundaries from a Single Image
Open accessAbstract
Occlusion reasoning, necessary for tasks such as navigation and object search, is an important aspect of everyday life and a fundamental problem in computer vision. We believe that the amazing ability of humans to reason about occlusions from one image is based on an intrinsically 3D interpretation. In this paper, our goal is to recover the occlusion boundaries and depth ordering of free-standing structures in the scene. Our approach is to learn to identify and label occlusion boundaries using the traditional edge and region cues together with 3D surface and depth cues. Since some of these cues require good spatial support (i.e., a segmentation), we gradually create larger regions and use them to improve inference over the boundaries. Our experiments demonstrate the power of a scene-based approach to occlusion reasoning.
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Robust Real-Time Face Detection
Viola, P., & Jones, M. J. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000013087.49260.fb · Cited by 14,097
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Understanding Line drawings of Scenes with Shadows
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Putting Objects in Perspective
Hoiem, D., Efros, A. A., & Hebert, M. (2008) · International Journal of Computer Vision · doi:10.1007/s11263-008-0137-5 · Cited by 803
Self-citationContextual Priming for Object Detection
Torralba, A. B. (2003) · International Journal of Computer Vision · doi:10.1023/a:1023052124951 · Cited by 792
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Recovering Surface Layout from an Image
Hoiem, D., Efros, A. A., & Hebert, M. (2007) · International Journal of Computer Vision · doi:10.1007/s11263-006-0031-y · Cited by 678
Self-citationUsing Multiple Segmentations to Discover Objects and their Extent in Image Collections
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3 of the 35 references couldn’t be matched to a known paper.
Research works printed but not linked: 3
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- gibson, 1968, Purple Perils, The perception of surface layout A classification of types
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Holistically-Nested Edge Detection
Xie, S., & Tu, Z. (2015) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.164 · Cited by 3,401
Unsupervised Monocular Depth Estimation with Left-Right Consistency
Godard, C., Aodha, O. M., & Brostow, G. J. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.699 · Cited by 3,270
Entropy rate superpixel segmentation
Liu, M.-Y., Tuzel, O., Ramalingam, S., & Chellappa, R. (2011) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2011.5995323 · Cited by 1,059
Zhang, J., & Tao, D. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2020.3039359 · Cited by 774
Decomposing a scene into geometric and semantically consistent regions
Gould, S. J., Fulton, R., & Koller, D. (2009) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2009.5459211 · Cited by 697
Metadata
- Authors
- Hoiem, D., Stein, A. N., Efros, A. A., & Hebert, M.
- Affiliations
- Carnegie Mellon University (US)
- Venue
- 2007 IEEE 11th International Conference on Computer Vision
- Publisher
- IEEE
- Published
- 2007
- Pages
- 1-8
- OpenAlex
- W2103380420
- Cited by
- 206
- References
- 35
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 5 · 2023: 4 · 2022: 3 · 2021: 8 · 2020: 9 · 2019: 3 · 2018: 4 · 2017: 7 · 2016: 15 · 2015: 19 · 2014: 14 · 2013: 17 · 2012: 14
- FWCI
- 17.24
- Type
- conference paper
- Language
- en
- Open access
- green
- figshare.com
- Licence
- cc-by
- Locations
- IEEE/CVF International Conference on Computer Vision (ICCV) (publishedVersion)
- KiltHub Repository (submittedVersion)
- Figshare (submittedVersion, cc-by)
- KiltHub Repository
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Keywords
- occlusion boundaries, occlusion reasoning, depth ordering, free-standing structures, depth cues, single image
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