A Hybrid Salient Object Detection with Global Context Awareness
Minglin Hong, Xiaolin Li, Jing Wang, Haiyang He, Shiguo Huang · 2020
Salient object detection methods focus on detecting precise salient objects and acquiring clear boundaries, but many approaches fail to achieve both of them. To solve this problem, we present A Hybrid Salient Object Detection with Global Context Awareness. The proposed model consists primarily of Multi-level Feature Enhancement (MFE) and Top-layer Processing (TP). MFE module is a module that fuses high-level features, low-level features and corresponding global context information and it is used for foreground enhancement. TP module generates two kinds of features, one is the representative top-layer features, and the other is the global context information that acts on the corresponding MFE module. Comparing our method with other 12 state-of-the-art salient object detection methods with different evaluation metrics, the experimental results show that our method is superior to other methods.