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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 6170 of 89 papers

TitleStatusHype
Global Optimality Guarantees for Nonconvex Unsupervised Video Segmentation0
A 3D Convolutional Approach to Spectral Object Segmentation in Space and TimeCode0
Key Instance Selection for Unsupervised Video Object Segmentation0
Learning Unsupervised Video Object Segmentation Through Visual AttentionCode0
Self-supervised Learning for Video Correspondence FlowCode0
Learning Correspondence from the Cycle-Consistency of TimeCode0
RVOS: End-to-End Recurrent Network for Video Object SegmentationCode0
Unsupervised Moving Object Detection via Contextual Information SeparationCode0
Unsupervised Video Object Segmentation with Distractor-Aware Online Adaptation0
Design Pseudo Ground Truth with Motion Cue for Unsupervised Video Object Segmentation0
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