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홈
SOTA
비지도 비디오 객체 분할
Unsupervised Video Object Segmentation On 10
Unsupervised Video Object Segmentation On 10
평가 지표
F
G
J
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
F
G
J
Paper Title
DEVA (DIS)
90.2
88.9
87.6
Tracking Anything with Decoupled Video Segmentation
GSANet
89.6
88.9
88.3
Guided Slot Attention for Unsupervised Video Object Segmentation
FakeFlow
89.0
88.5
88.0
Improving Unsupervised Video Object Segmentation via Fake Flow Generation
DPA
88.4
87.6
86.8
Dual Prototype Attention 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
AMP
87.5
87.3
87.1
Adaptive Multi-source Predictor for Zero-shot Video Object Segmentation
IMP
86.7
85.6
84.5
Iteratively Selecting an Easy Reference Frame Makes Unsupervised Video Object Segmentation Easier
DLDA
86.6
85.75
84.9
Self-supervised Video Object Segmentation with Distillation Learning of Deformable Attention
TMO (RN-101)
86.6
86.1
85.6
Treating Motion as Option to Reduce Motion Dependency in Unsupervised Video Object Segmentation
D2Conv3D
86.5
86.0
85.5
D2Conv3D: Dynamic Dilated Convolutions for Object Segmentation in Videos
PMN
86.4
85.9
85.4
Unsupervised Video Object Segmentation via Prototype Memory Network
TransportNet
85.0
84.8
84.5
Deep Transport Network for Unsupervised Video Object Segmentation
RTNet
84.7
85.2
85.6
Reciprocal Transformations for Unsupervised Video Object Segmentation
3DC-Seg
84.7
84.5
84.3
Making a Case for 3D Convolutions for Object Segmentation in Videos
AMC-Net
84.6
84.6
84.5
Learning Motion-Appearance Co-Attention for Zero-Shot Video Object Segmentation
FSNet
83.1
83.3
83.4
Full-Duplex Strategy for Video Object Segmentation
DFNet
81.8
82.6
83.4
Learning Discriminative Feature with CRF for Unsupervised Video Object Segmentation
MATNet
80.7
81.6
82.4
Motion-Attentive Transition for Zero-Shot Video Object Segmentation
WCS-Net
80.7
81.5
82.2
Unsupervised Video Object Segmentation with Joint Hotspot Tracking
AD-Net
80.5
81.1
81.7
Anchor Diffusion for Unsupervised Video Object Segmentation
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