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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 2130 of 48 papers

TitleStatusHype
Full-Duplex Strategy for Video Object SegmentationCode1
Guidance and Teaching Network for Video Salient Object Detection0
Confidence-guided Adaptive Gate and Dual Differential Enhancement for Video Salient Object Detection0
Video Salient Object Detection via Adaptive Local-Global RefinementCode0
Weakly Supervised Video Salient Object DetectionCode1
Dynamic Context-Sensitive Filtering Network for Video Salient Object DetectionCode1
DS-Net: Dynamic Spatiotemporal Network for Video Salient Object DetectionCode1
Fast Video Salient Object Detection via Spatiotemporal Knowledge Distillation0
Exploring Rich and Efficient Spatial Temporal Interactions for Real Time Video Salient Object DetectionCode1
A Novel Video Salient Object Detection Method via Semi-supervised Motion Quality PerceptionCode0
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