Learning long-term structural dependencies for video salient object detection

• Main Authors: WANG, Bo, LIU, Wenxi, HAN, Guoqiang, HE, Shengfeng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Predictive models; Object detection; Feature extraction; Saliency detection; Convolution; Merging; Object recognition; Video salient object detection; graph convolutional network; supervoxel; Information Security
• Online Access: https://ink.library.smu.edu.sg/sis_research/7871
• Institution: Singapore Management University

Existing video salient object detection (VSOD) methods focus on exploring either short-term or long-term temporal information. However, temporal information is exploited in a global frame-level or regular grid structure, neglecting inter-frame structural dependencies. In this article, we propose to...