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Video Saliency Detection
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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.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Saliency Detection in Educational Videos: Analyzing the Performance of Current Models, Identifying Limitations and Advancement Directions
ViDSOD-100: A New Dataset and a Baseline Model for RGB-D Video Salient Object Detection
An Integrated System for Spatio-Temporal Summarization of 360-degrees Videos
Panoramic Vision Transformer for Saliency Detection in 360° Videos
A Comprehensive Survey on Video Saliency Detection with Auditory Information: the Audio-visual Consistency Perceptual is the Key!
GASP: Gated Attention For Saliency Prediction
Weakly Supervised Visual-Auditory Fixation Prediction with Multigranularity Perception
Temporal-Spatial Feature Pyramid for Video Saliency Detection
Weakly Supervised Video Salient Object Detection
ViNet: Pushing the limits of Visual Modality for Audio-Visual Saliency Prediction
Hierarchical Domain-Adapted Feature Learning for Video Saliency Prediction
Exploring Rich and Efficient Spatial Temporal Interactions for Real Time Video Salient Object Detection
A Plug-and-play Scheme to Adapt Image Saliency Deep Model for Video Data
Unified Image and Video Saliency Modeling
Video Saliency Prediction Using Enhanced Spatiotemporal Alignment Network
TASED-Net: Temporally-Aggregating Spatial Encoder-Decoder Network for Video Saliency Detection
Simple vs complex temporal recurrences for video saliency prediction
A Dilated Inception Network for Visual Saliency Prediction
Contextual Encoder-Decoder Network for Visual Saliency Prediction
Unsupervised uncertainty estimation using spatiotemporal cues in video saliency detection
Global and Local Sensitivity Guided Key Salient Object Re-augmentation for Video Saliency Detection
Salient Object Detection in Video using Deep Non-Local Neural Networks
SG-FCN: A Motion and Memory-Based Deep Learning Model for Video Saliency Detection
Video Saliency Detection by 3D Convolutional Neural Networks
Review of Visual Saliency Detection with Comprehensive Information
Revisiting Video Saliency: A Large-scale Benchmark and a New Model
Graph-Theoretic Spatiotemporal Context Modeling for Video Saliency Detection
Visual Saliency Based on Scale-Space Analysis in the Frequency Domain
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