preprintJun 1, 2016Closed access

Deep Saliency with Encoded Low Level Distance Map and High Level Features

Kootenay Association for Science & Technology · Korea Advanced Institute of Science and Technology · +1 more institution

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Abstract

Recent advances in saliency detection have utilized deep learning to obtain high level features to detect salient regions in a scene. These advances have demonstrated superior results over previous works that utilize hand-crafted low level features for saliency detection. In this paper, we demonstrate that hand-crafted features can provide complementary information to enhance performance of saliency detection that utilizes only high level features. Our method utilizes both high level and low level features for saliency detection under a unified deep learning framework. The high level features are extracted using the VGG-net, and the low level features are compared with other parts of an image to form a low…

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