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Unsupervised Video Object Segmentation

The unsupervised scenario assumes that the user does not interact with the algorithm to obtain the segmentation masks. Methods should provide a set of object candidates with no overlapping pixels that span through the whole video sequence. This set of objects should contain at least the objects that capture human attention when watching the whole video sequence i.e objects that are more likely to be followed by human gaze.

Papers

Showing 7180 of 89 papers

TitleStatusHype
Video Object Segmentation using Teacher-Student Adaptation in a Human Robot Interaction (HRI) SettingCode0
Unsupervised Online Video Object Segmentation with Motion Property UnderstandingCode0
Unsupervised Video Object Segmentation using Motion Saliency-Guided Spatio-Temporal Propagation0
Unsupervised Video Object Segmentation with Motion-based Bilateral Networks0
Pyramid Dilated Deeper ConvLSTM for Video Salient Object Detection0
Extending Layered Models to 3D MotionCode0
Unsupervised Video Object Segmentation for Deep Reinforcement LearningCode0
Adversarial Framework for Unsupervised Learning of Motion Dynamics in Videos0
Instance Embedding Transfer to Unsupervised Video Object Segmentation0
Learning to Segment Moving Objects0
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