PSNet: Parallel Symmetric Network for Video Salient Object Detection
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Abstract (arXiv)
For the video salient object detection (VSOD) task, how to excavate the information from the appearance modality and the motion modality has always been a topic of great concern. The two-stream structure, including an RGB appearance stream and an optical flow motion stream, has been widely used as a typical pipeline for VSOD tasks, but the existing methods usually only use motion features to unidirectionally guide appearance features or adaptively but blindly fuse two modality features. However, these methods underperform in diverse scenarios due to the uncomprehensive and unspecific learning schemes. In this paper, following a more secure modeling philosophy, we deeply investigate the importance of appearance modality and motion modality in a more comprehensive way and propose a VSOD network with up and down parallel symmetry, named PSNet. Two parallel branches with different dominant modalities are set to achieve complete video saliency decoding with the cooperation of the Gather Diffusion Reinforcement (GDR) module and Cross-modality Refinement and Complement (CRC) module. Finally, we use the Importance Perception Fusion (IPF) module to fuse the features from two parallel branches according to their different importance in different scenarios. Experiments on four dataset benchmarks demonstrate that our method achieves desirable and competitive performance.
Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Builds on 59 of its 111 references that are in the map. First posted on arXiv 12 Oct 2022.
Builds on
59 of 111 references.
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38 more
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50 most cited of 59 All 59 (JSON)
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Citing papers per year: 2022: 2; 2023: 7; 2024: 1; 2025: 2.
12 papers.
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- 2023Advances in Deep Concealed Scene Understandingcited by 47
- 2023Frequency Perception Network for Camouflaged Object Detectioncited by 37
- 2023Point-aware Interaction and CNN-induced Refinement Network for RGB-D Salient Object Detectioncited by 25
- 2022Multi-Projection Fusion and Refinement Network for Salient Object Detection in 360deg Omnidirectional Imagecited by 13
- 2023SDDNet: Style-guided Dual-layer Disentanglement Network for Shadow Detectioncited by 11
- 2025From Sight to Insight: Unleashing Eye-Tracking in Weakly Supervised Video Salient Object Detectioncited by 3
- 2022Feedback Chain Network For Hippocampus Segmentationcited by 1
- 2023PV-SSD: A Multi-Modal Point Cloud Feature Fusion Method for Projection Features and Variable Receptive Field Voxel Featurescited by 1
- 2024Relevance-guided Audio Visual Fusion for Video Saliency Predictioncited by 1
- 2025GAPNet: A Lightweight Framework for Image and Video Salient Object Detection via Granularity-Aware Paradigmcited by 1
- 2023Towards Imbalanced Motion: Part-Decoupling Network for Video Portrait Segmentationcited by 0
- 2025GAPNet: A Lightweight Framework for Image and Video Salient Object Detection via Granularity-Aware Paradigm11 Aug 2025
- 2025From Sight to Insight: Unleashing Eye-Tracking in Weakly Supervised Video Salient Object Detection30 Jun 2025
- 2024Relevance-guided Audio Visual Fusion for Video Saliency Prediction18 Nov 2024
- 2023SDDNet: Style-guided Dual-layer Disentanglement Network for Shadow Detection17 Aug 2023
- 2023Point-aware Interaction and CNN-induced Refinement Network for RGB-D Salient Object Detection17 Aug 2023
- 2023Frequency Perception Network for Camouflaged Object Detection17 Aug 2023
- 2023PV-SSD: A Multi-Modal Point Cloud Feature Fusion Method for Projection Features and Variable Receptive Field Voxel Features13 Aug 2023
- 2023Towards Imbalanced Motion: Part-Decoupling Network for Video Portrait Segmentation31 Jul 2023
- 2023PUGAN: Physical Model-Guided Underwater Image Enhancement Using GAN with Dual-Discriminators15 Jun 2023
- 2023Advances in Deep Concealed Scene Understanding21 Apr 2023
- 2022Multi-Projection Fusion and Refinement Network for Salient Object Detection in 360deg Omnidirectional Image23 Dec 2022
- 2022Feedback Chain Network For Hippocampus Segmentation15 Nov 2022