DS-Net: Dynamic Spatiotemporal Network for Video Salient Object Detection

by   Yuting Su, et al.

As moving objects always draw more attention of human eyes, the temporal motive information is always exploited complementarily with spatial information to detect salient objects in videos. Although efficient tools such as optical flow have been proposed to extract temporal motive information, it often encounters difficulties when used for saliency detection due to the movement of camera or the partial movement of salient objects. In this paper, we investigate the complimentary roles of spatial and temporal information and propose a novel dynamic spatiotemporal network (DS-Net) for more effective fusion of spatiotemporal information. We construct a symmetric two-bypass network to explicitly extract spatial and temporal features. A dynamic weight generator (DWG) is designed to automatically learn the reliability of corresponding saliency branch. And a top-down cross attentive aggregation (CAA) procedure is designed so as to facilitate dynamic complementary aggregation of spatiotemporal features. Finally, the features are modified by spatial attention with the guidance of coarse saliency map and then go through decoder part for final saliency map. Experimental results on five benchmarks VOS, DAVIS, FBMS, SegTrack-v2, and ViSal demonstrate that the proposed method achieves superior performance than state-of-the-art algorithms. The source code is available at https://github.com/TJUMMG/DS-Net.


page 1

page 3

page 7

page 9


Video Saliency Detection by 3D Convolutional Neural Networks

Different from salient object detection methods for still images, a key ...

Video Salient Object Detection via Fully Convolutional Networks

This paper proposes a deep learning model to efficiently detect salient ...

Exploring Rich and Efficient Spatial Temporal Interactions for Real Time Video Salient Object Detection

The current main stream methods formulate their video saliency mainly fr...

Exploring Spatial-Temporal Features for Deepfake Detection and Localization

With the continuous research on Deepfake forensics, recent studies have ...

A Gated Fusion Network for Dynamic Saliency Prediction

Predicting saliency in videos is a challenging problem due to complex mo...

DC-Net: Divide-and-Conquer for Salient Object Detection

In this paper, we introduce Divide-and-Conquer into the salient object d...

Summarize and Search: Learning Consensus-aware Dynamic Convolution for Co-Saliency Detection

Humans perform co-saliency detection by first summarizing the consensus ...

Please sign up or login with your details

Forgot password? Click here to reset