HyperAI
الرئيسية
الأخبار
أحدث الأوراق البحثية
الدروس
مجموعات البيانات
الموسوعة
SOTA
نماذج LLM
لوحة الأداء GPU
الفعاليات
البحث
حول
العربية
HyperAI
Toggle sidebar
البحث في الموقع...
⌘
K
الرئيسية
SOTA
Unsupervised Video Object Segmentation
Unsupervised Video Object Segmentation On 10
Unsupervised Video Object Segmentation On 10
المقاييس
F
G
J
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
Columns
اسم النموذج
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
0 of 25 row(s) selected.
Previous
Next