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Video Saliency Detection

Video Saliency Detection is the process of detecting or predicting the most visually important or attention-grabbing regions in video sequence. This regions are where humans most likely focus their attention when watching the video.

Papers

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Showing 1–25 of 36 papers

TitleStatusHype
From Semantic Categories to Fixations: A Novel Weakly-Supervised Visual-Auditory Saliency Detection ApproachCode1
GASP: Gated Attention For Saliency PredictionCode1
Weakly Supervised Visual-Auditory Fixation Prediction with Multigranularity PerceptionCode1
Weakly Supervised Video Salient Object DetectionCode1
Video Saliency Prediction Using Enhanced Spatiotemporal Alignment NetworkCode1
ViNet: Pushing the limits of Visual Modality for Audio-Visual Saliency PredictionCode1
Panoramic Vision Transformer for Saliency Detection in 360° VideosCode1
Hierarchical Domain-Adapted Feature Learning for Video Saliency PredictionCode1
Unified Image and Video Saliency ModelingCode1
AIM 2024 Challenge on Video Saliency Prediction: Methods and ResultsCode1
Exploring Rich and Efficient Spatial Temporal Interactions for Real Time Video Salient Object DetectionCode1
Review of Visual Saliency Detection with Comprehensive Information—0
A model of saliency-based visual attention for rapid scene analysis—0
Encoding Based Saliency Detection for Videos and Images—0
Global and Local Sensitivity Guided Key Salient Object Re-augmentation for Video Saliency Detection—0
Graph-Based Visual Saliency—0
Graph-Theoretic Spatiotemporal Context Modeling for Video Saliency Detection—0
Learning to Explore Intrinsic Saliency for Stereoscopic Video—0
Saliency Detection in 360° Videos—0
Saliency Detection in Educational Videos: Analyzing the Performance of Current Models, Identifying Limitations and Advancement Directions—0
Salient Object Detection in Video using Deep Non-Local Neural Networks—0
SG-FCN: A Motion and Memory-Based Deep Learning Model for Video Saliency Detection—0
Temporal-Spatial Feature Pyramid for Video Saliency Detection—0
Unsupervised uncertainty estimation using spatiotemporal cues in video saliency detection—0
Video Saliency Detection by 3D Convolutional Neural Networks—0
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