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SOTA
无监督视频物体分割
Unsupervised Video Object Segmentation On 12
Unsupervised Video Object Segmentation On 12
评估指标
J
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
J
Paper Title
Repository
TMO (MiT-b1)
71.1
Treating Motion as Option to Reduce Motion Dependency in Unsupervised Video Object Segmentation
-
WCS-Net
70.5
Unsupervised Video Object Segmentation with Joint Hotspot Tracking
-
TMO++ (RN-101)
73.1
Treating Motion as Option with Output Selection for Unsupervised Video Object Segmentation
-
PDB
65.5
Pyramid Dilated Deeper ConvLSTM for Video Salient Object Detection
-
MATNet
69.0
Motion-Attentive Transition for Zero-Shot Video Object Segmentation
-
AGNN
70.8
Zero-Shot Video Object Segmentation via Attentive Graph Neural Networks
-
RTNet
70.1
Reciprocal Transformations for Unsupervised Video Object Segmentation
TMO (RN-101)
71.5
Treating Motion as Option to Reduce Motion Dependency in Unsupervised Video Object Segmentation
-
TMO++ (MiT-b1, MS)
73.5
Treating Motion as Option with Output Selection for Unsupervised Video Object Segmentation
-
AMP
75.0
Adaptive Multi-source Predictor for Zero-shot Video Object Segmentation
-
FakeFlow
75.1
Improving Unsupervised Video Object Segmentation via Fake Flow Generation
-
DPA
73.7
Dual Prototype Attention for Unsupervised Video Object Segmentation
-
COSNet
70.5
See More, Know More: Unsupervised Video Object Segmentation with Co-Attention Siamese Networks
-
AMC-Net
71.1
Learning Motion-Appearance Co-Attention for Zero-Shot Video Object Segmentation
-
AGS
69.7
Learning Unsupervised Video Object Segmentation Through Visual Attention
-
TMO++ (MiT-b1)
73.0
Treating Motion as Option with Output Selection for Unsupervised Video Object Segmentation
-
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