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Context based object categorization: A critical survey
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“Many different types of context have been discussed (Divvala et al. 2009;Galleguillos and Belongie 2010), and can broadly be grouped into one of three categories: 1. Semantic context: The likelihood of an object to be found in some scenes, but not in others; 2. Spatial context: The likelihood of finding an object in some position and not others with respect to other objects in the scene; 3. Scale”
From Deep Learning for Generic Object Detection: A Survey (2020) · cites this paper as Galleguillos and Belongie 2010
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Deep Learning for Generic Object Detection: A Survey
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Metadata
- Authors
- Galleguillos, C., & Belongie, S.
- Affiliations
- University of California San Diego (US)
- California Institute of Technology (US)
- Corresponding author
- Galleguillos, Carolina
- Venue
- Computer Vision and Image Understanding
- Publisher
- Elsevier BV
- Published
- 2010-06
- Volume
- 114
- Issue
- 6
- Pages
- 712-722
- ISSN
- 1077-3142 (ISSN-L)
- OpenAlex
- W2111868822
- Cited by
- 351
- References
- 41
- Citations by year
- 2026: 6 · 2025: 12 · 2024: 9 · 2023: 8 · 2022: 12 · 2021: 23 · 2020: 26 · 2019: 30 · 2018: 25 · 2017: 27 · 2016: 28 · 2015: 31 · 2014: 35 · 2013: 24 · 2012: 20
- FWCI
- 28.95
- Type
- journal article
- Language
- en
- Open access
- green
- escholarship.org
- Locations
- Computer Vision and Image Understanding (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- CaltechAUTHORS (California Institute of Technology) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image and Video Retrieval Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Visual Attention and Saliency Detection
- Keywords
- object classification, context modeling, object recognition, contextual information, occlusion, appearance-based recognition, scene statistics, context-aware interaction, scalability
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