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Most Influential CVPR 2010 Paper · 2026-03 edition

Context-aware Saliency Detection

S. Goferman; L. Zelnik-Manor and A. Tal

Venue
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2010
Recognition
Most Influential CVPR 2010 Paper (Rank No. 5)
Edition
2026-03
Impact factor
9
Certificate ID
c852c7106ccc283d

Abstract

We propose a new type of saliency - context-aware saliency - which aims at detecting the image regions that represent the scene. This definition differs from previous definitions whose goal is to either identify fixation points or detect the dominant object. In accordance with our saliency definition, we present a detection algorithm which is based on four principles observed in the psychological literature. The benefits of the proposed approach are evaluated in two applications where the context of the dominant objects is just as essential as the objects themselves. In image retargeting we demonstrate that using our saliency prevents distortions in the important regions. In summarization we show that our saliency helps to produce compact, appealing, and informative summaries.

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