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Most Influential CVPR 2007 Paper · 2026-03 edition

Saliency Detection: A Spectral Residual Approach

X. Hou and L. Zhang

Venue
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2007
Recognition
Most Influential CVPR 2007 Paper (Rank No. 1)
Edition
2026-03
Impact factor
10
Certificate ID
323a427516c39b07

Abstract

The ability of human visual system to detect visual saliency is extraordinarily fast and reliable. However, computational modeling of this basic intelligent behavior still remains a challenge. This paper presents a simple method for the visual saliency detection. Our model is independent of features, categories, or other forms of prior knowledge of the objects. By analyzing the log-spectrum of an input image, we extract the spectral residual of an image in spectral domain, and propose a fast method to construct the corresponding saliency map in spatial domain. We test this model on both natural pictures and artificial images such as psychological patterns. The result indicate fast and robust saliency detection of our method.

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