A Convolutional Encoder-Decoder Network With Skip Connections for Saliency Prediction

A Convolutional Encoder-Decoder Network With Skip Connections for Saliency Prediction

In this paper, we propose a novel convolutional encoder-decoder network with skip connections, named CEDNS, to improve the performance of saliency prediction. The encoder network utilizes the DenseNet model as the stem network to extract abundant hierarchical features from input images. Subsequently...

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Bibliographic Details
Main Authors: Fei Qi, Chunhuan Lin, Guangming Shi, Hao Li
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Saliency
convolutional neural networks
encoder-decoder
skip connections
visual attention
Online Access:https://ieeexplore.ieee.org/document/8709735/

Internet

https://ieeexplore.ieee.org/document/8709735/

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