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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 1120 of 48 papers

TitleStatusHype
Depth-Cooperated Trimodal Network for Video Salient Object DetectionCode1
Full-Duplex Strategy for Video Object SegmentationCode1
Video Salient Object Detection via Adaptive Local-Global RefinementCode0
ViDSOD-100: A New Dataset and a Baseline Model for RGB-D Video Salient Object DetectionCode0
A Novel Video Salient Object Detection Method via Semi-supervised Motion Quality PerceptionCode0
Motion-aware Memory Network for Fast Video Salient Object DetectionCode0
Semi-Supervised Video Salient Object Detection Using Pseudo-LabelsCode0
Motion Guided Attention for Video Salient Object DetectionCode0
Real-Time Salient Object Detection With a Minimum Spanning TreeCode0
Shifting More Attention to Video Salient Object DetectionCode0
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