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Video Salient Object Detection

Video salient object detection (VSOD) is significantly essential for understanding the underlying mechanism behind HVS during free-viewing in general and instrumental to a wide range of real-world applications, e.g., video segmentation, video captioning, video compression, autonomous driving, robotic interaction, weakly supervised attention. Besides its academic value and practical significance, VSOD presents great difficulties due to the challenges carried by video data (diverse motion patterns, occlusions, blur, large object deformations, etc.) and the inherent complexity of human visual attention behavior (i.e., selective attention allocation, attention shift) during dynamic scenes. Online benchmark: http://dpfan.net/davsod.

( Image credit: Shifting More Attention to Video Salient Object Detection, CVPR2019-Best Paper Finalist )

Papers

Showing 3140 of 48 papers

TitleStatusHype
A Novel Video Salient Object Detection Method via Semi-supervised Motion Quality PerceptionCode0
TENet: Triple Excitation Network for Video Salient Object Detection0
Motion Guided Attention for Video Salient Object DetectionCode0
Semi-Supervised Video Salient Object Detection Using Pseudo-LabelsCode0
Time Masking: Leveraging Temporal Information in Spoken Dialogue Systems0
Shifting More Attention to Video Salient Object DetectionCode0
Salient Object Detection in Video using Deep Non-Local Neural Networks0
Unsupervised Video Object Segmentation using Motion Saliency-Guided Spatio-Temporal Propagation0
Pyramid Dilated Deeper ConvLSTM for Video Salient Object Detection0
Sequential Clique Optimization for Video Object Segmentation0
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