TY - GEN
T1 - Learning the Spiral Sharing Network with Minimum Salient Region Regression for Saliency Detection
AU - Chen, Zukai
AU - Tan, Xin
AU - Zhu, Hengliang
AU - DIng, Shouhong
AU - Ma, Lizhuang
AU - Song, Haichuan
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/5
Y1 - 2019/5
N2 - With the development of convolutional neural networks (CNNs), saliency detection methods have made a big progress in recent years. However, the previous methods sometimes mistakenly highlight the non-salient region, especially in complex backgrounds. To solve this problem, a two-stage method for saliency detection is proposed in this paper. In the first stage, a network is used to regress the minimum salient region (RMSR) containing all salient objects. Then in the second stage, in order to fuse the multi-level features, the spiral sharing network (SSN) is proposed for pixel-level detection on the result of RMSR. Experimental results on four public datasets show that our model is effective over the state-of-the-art approaches.
AB - With the development of convolutional neural networks (CNNs), saliency detection methods have made a big progress in recent years. However, the previous methods sometimes mistakenly highlight the non-salient region, especially in complex backgrounds. To solve this problem, a two-stage method for saliency detection is proposed in this paper. In the first stage, a network is used to regress the minimum salient region (RMSR) containing all salient objects. Then in the second stage, in order to fuse the multi-level features, the spiral sharing network (SSN) is proposed for pixel-level detection on the result of RMSR. Experimental results on four public datasets show that our model is effective over the state-of-the-art approaches.
KW - saliency detection
KW - salient region
KW - spiral sharing network
UR - https://www.scopus.com/pages/publications/85068958650
U2 - 10.1109/ICASSP.2019.8682531
DO - 10.1109/ICASSP.2019.8682531
M3 - 会议稿件
AN - SCOPUS:85068958650
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 1667
EP - 1671
BT - 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019
Y2 - 12 May 2019 through 17 May 2019
ER -