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Cited by 171

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Statistical context priming for object detection

Torralba, A., Sinha, P.·2002·Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001

Abstract

There is general consensus that context can be a rich source of information about an object's identity, location and scale. However the issue of how to formalize centextual influences is still largely open. Here we introduce a simple probabilistic framework for modeling the relationship between context and object properties. We represent global context information in terms of the spatial layout of spectral components. The resulting scheme serves as an effective procedure for context driven focus of attention and scale-selection on real-world scenes. Based on a simple holistic analysis of an image, the scheme is able to accurately predict object locations and sizes.

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Metadata

Authors
Torralba, A., & Sinha, P.
Venue
Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001
Published
2002-11-13
Volume
1
Pages
763-770
OpenAlex
W2134789565
Cited by
171
References
1
FWCI
7.44
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Statistical context priming for object detection. https://app.cochat.ai/papers/10.1109/iccv.2001.937604
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Torralba, A., & Sinha, P. (2002). Statistical context priming for object detection. Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001. https://doi.org/10.1109/iccv.2001.937604

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