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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Flagged first, then by citations
3 of the 35 references couldn’t be matched to a known paper.
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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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