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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

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Showing 51–89 of 89 papers

TitleStatusHype
Motion-Attentive Transition for Zero-Shot Video Object SegmentationCode1
MAST: A Memory-Augmented Self-supervised TrackerCode1
Zero-Shot Video Object Segmentation via Attentive Graph Neural NetworksCode1
See More, Know More: Unsupervised Video Object Segmentation with Co-Attention Siamese NetworksCode1
UnOVOST: Unsupervised Offline Video Object Segmentation and TrackingCode1
Anchor Diffusion for Unsupervised Video Object SegmentationCode0
EpO-Net: Exploiting Geometric Constraints on Dense Trajectories for Motion SaliencyCode0
Joint-task Self-supervised Learning for Temporal CorrespondenceCode0
Semi-Supervised Video Salient Object Detection Using Pseudo-LabelsCode0
Global Optimality Guarantees for Nonconvex Unsupervised Video Segmentation—0
A 3D Convolutional Approach to Spectral Object Segmentation in Space and TimeCode0
Key Instance Selection for Unsupervised Video Object Segmentation—0
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 Adaptation—0
Design Pseudo Ground Truth with Motion Cue for Unsupervised Video Object Segmentation—0
Tukey-Inspired Video Object SegmentationCode1
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 Propagation—0
Unsupervised Video Object Segmentation with Motion-based Bilateral Networks—0
Pyramid Dilated Deeper ConvLSTM for Video Salient Object Detection—0
Extending Layered Models to 3D MotionCode0
Unsupervised Video Object Segmentation for Deep Reinforcement LearningCode0
Adversarial Framework for Unsupervised Learning of Motion Dynamics in Videos—0
Instance Embedding Transfer to Unsupervised Video Object Segmentation—0
Learning to Segment Moving Objects—0
SegFlow: Joint Learning for Video Object Segmentation and Optical FlowCode0
Primary Object Segmentation in Videos Based on Region Augmentation and Reduction—0
Learning Video Object Segmentation with Visual Memory—0
Video Object Segmentation using Supervoxel-Based GerrymanderingCode0
FusionSeg: Learning to combine motion and appearance for fully automatic segmention of generic objects in videos—0
Learning Motion Patterns in Videos—0
Primary Object Segmentation in Videos via Alternate Convex Optimization of Foreground and Background Distributions—0
Motion Trajectory Segmentation via Minimum Cost Multicuts—0
Causal Video Object Segmentation From Persistence of Occlusions—0
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