• DOI:10.1109/TIP.2016.2579306
Corpus ID: 99982

DeepSaliency: Multi-Task Deep Neural Network Model for Salient Object Detection

@article{Li2016DeepSaliencyMD,
  title={DeepSaliency: Multi-Task Deep Neural Network Model for Salient Object Detection},
  author={Xi Li and Liming Zhao and Lina Wei and Ming-Hsuan Yang and Fei Wu and Y. Zhuang and Haibin Ling and Jingdong Wang},
  journal={IEEE Transactions on Image Processing},
  year={2016},
  volume={25},
  pages={3919-3930}
}

Xi Li, Liming Zhao, +5 authors Jingdong Wang

Published 2016

Computer Science, Medicine

IEEE Transactions on Image Processing

A key problem in salient object detection is how to effectively model the semantic properties of salient objects in a data-driven manner. In this paper, we propose a multi-task deep saliency model based on a fully convolutional neural network with global input (whole raw images) and global output (whole saliency maps). In principle, the proposed saliency model takes a data-driven strategy for encoding the underlying saliency prior information, and then sets up a multi-task learning scheme for… CONTINUE READING

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