Saliency Detection with Recurrent Fully Convolutional Networks

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Authors Linzhao Wang, Lijun Wang, Huchuan Lu, Pingping Zhang, Xiang Ruan
Journal/Conference Name ECCV
Paper Category
Paper Abstract • Employs three kind of low-level contrast features, including color, intensity and orientation, and the center prior knowledge to introduce saliency prior maps. • Train the RFCN with two stage training strategy, pre-training on the segmentation data set and fine-tuning on the saliency data set. The recurrent structure can incorporate the saliency prior maps into the CNNs with an end-to-end training method. • Refine the saliency maps with a postprocessing method which can improve the performance of RFCN. Edge-preserving maps are produced with the computation of color confidence and spatial confidence. 3. Algorithm 4. Results
Date of publication 2016
Code Programming Language MATLAB

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