Saliency detection via bi-directional propagation
Xu, Yingyue; Hong, Xiaopeng; Liu, Xin; Zhao, Guoying (2018-03-14)
Yingyue Xu, Xiaopeng Hong, Xin Liu, Guoying Zhao. Saliency detection via bi-directional propagation. Journal of Visual Communication and Image Representation, Volume 53, 2018, Pages 113-121, ISSN 1047-3203. https://doi.org/10.1016/j.jvcir.2018.02.015
© 2018 Elsevier Inc. All rights reserved. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
https://creativecommons.org/licenses/by-nc-nd/4.0/
https://urn.fi/URN:NBN:fi-fe201902266253
Tiivistelmä
Abstract
Recent saliency models rely on propagation to compute the saliency map. Previous propagation methods are single directional, where foreground propagation and background propagation are separate (e.g., only foreground propagation, or background propagation after foreground propagation). Different from the previous approaches, we propose a bi-directional propagation model (BIP) for saliency detection. The BIP model propagates from the labeled foreground superpixels and the labeled background superpixels to the unlabeled ones in the same iteration. A difficulty-based rule is adopted to manipulate the prorogation sequence, which considers both the distinctness of the superpixel to its neighboring ones and its connectivity to the labeled sets. The BIP model outperforms fourteen state-of-the-art saliency models on four challenging datasets, and largely enhances the propagation efficiency compared to single directional propagation models.
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