Unsupervised Video Object Segmentation On 10

Metrics

Results

Performance results of various models on this benchmark

Model Name	F	G	J	Paper Title	Repository
RTNet	84.7	85.2	85.6	Reciprocal Transformations for Unsupervised Video Object Segmentation
FakeFlow	89.0	88.5	88.0	Improving Unsupervised Video Object Segmentation via Fake Flow Generation
IMP	86.7	85.6	84.5	Iteratively Selecting an Easy Reference Frame Makes Unsupervised Video Object Segmentation Easier	-
TransportNet	85.0	84.8	84.5	Deep Transport Network for Unsupervised Video Object Segmentation	-
TMO (MiT-b1)	87.8	87.2	86.6	Treating Motion as Option to Reduce Motion Dependency in Unsupervised Video Object Segmentation
AGS	77.4	78.6	79.7	Learning Unsupervised Video Object Segmentation Through Visual Attention	-
PDB	74.5	75.9	77.2	Pyramid Dilated Deeper ConvLSTM for Video Salient Object Detection	-
3DC-Seg	84.7	84.5	84.3	Making a Case for 3D Convolutions for Object Segmentation in Videos
GSANet	89.6	88.9	88.3	Guided Slot Attention for Unsupervised Video Object Segmentation
DLDA	86.6	85.75	84.9	Self-supervised Video Object Segmentation with Distillation Learning of Deformable Attention	-
AGNN	79.1	79.9	80.7	Zero-Shot Video Object Segmentation via Attentive Graph Neural Networks
PMN	86.4	85.9	85.4	Unsupervised Video Object Segmentation via Prototype Memory Network
TMO (RN-101)	86.6	86.1	85.6	Treating Motion as Option to Reduce Motion Dependency in Unsupervised Video Object Segmentation
AMP	87.5	87.3	87.1	Adaptive Multi-source Predictor for Zero-shot Video Object Segmentation
DEVA (DIS)	90.2	88.9	87.6	Tracking Anything with Decoupled Video Segmentation
MATNet	80.7	81.6	82.4	Motion-Attentive Transition for Zero-Shot Video Object Segmentation
AMC-Net	84.6	84.6	84.5	Learning Motion-Appearance Co-Attention for Zero-Shot Video Object Segmentation	-
D2Conv3D	86.5	86.0	85.5	D2Conv3D: Dynamic Dilated Convolutions for Object Segmentation in Videos
DFNet	81.8	82.6	83.4	Learning Discriminative Feature with CRF for Unsupervised Video Object Segmentation	-
FSNet	83.1	83.3	83.4	Full-Duplex Strategy for Video Object Segmentation

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