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المنصة
الرئيسية
SOTA
رؤية حاسوبية
Video Instance Segmentation On Youtube Vis 2
Video Instance Segmentation On Youtube Vis 2
المقاييس
AP50
AP75
AR1
AR10
mask AP
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
Columns
اسم النموذج
AP50
AP75
AR1
AR10
mask AP
Paper Title
CAVIS(VIT-L, Offline)
87.3
73.2
49.7
70.3
65.3
Context-Aware Video Instance Segmentation
DVIS++(VIT-L, Offline)
86.7
71.5
48.8
69.5
63.9
DVIS++: Improved Decoupled Framework for Universal Video Segmentation
DVIS-DAQ(VIT-L, Offline)
86.1
72.2
49.6
70.7
64.5
DVIS-DAQ: Improving Video Segmentation via Dynamic Anchor Queries
RefineVIS (Swin-L, online)
84.1
68.5
48.3
65.2
61.4
RefineVIS: Video Instance Segmentation with Temporal Attention Refinement
DVIS(Swin-L)
83.0
68.4
47.7
65.7
60.1
DVIS: Decoupled Video Instance Segmentation Framework
DVIS++(VIT-L, Online)
82.7
70.2
49.5
68.0
62.3
DVIS++: Improved Decoupled Framework for Universal Video Segmentation
NOVIS (Swin-L)
82.0
66.5
47.9
64.4
59.8
NOVIS: A Case for End-to-End Near-Online Video Instance Segmentation
TarViS (Swin-L)
81.4
67.6
47.6
64.8
60.2
TarViS: A Unified Approach for Target-based Video Segmentation
GRAtt-VIS (Swin-L)
81.3
67.1
48.8
64.5
60.3
GRAtt-VIS: Gated Residual Attention for Auto Rectifying Video Instance Segmentation
GenVIS (Swin-L)
80.9
66.5
49.1
64.7
60.1
A Generalized Framework for Video Instance Segmentation
IDOL (Swin-L)
80.8
63.5
45
60.1
56.1
In Defense of Online Models for Video Instance Segmentation
MDQE(Swin-L)
80.7
61.7
45.4
60.6
55.5
MDQE: Mining Discriminative Query Embeddings to Segment Occluded Instances on Challenging Videos
VITA (Swin-L)
80.6
61.0
47.7
62.6
57.5
VITA: Video Instance Segmentation via Object Token Association
UniVS(Swin-L)
79.4
63.3
46.2
63.1
57.9
UniVS: Unified and Universal Video Segmentation with Prompts as Queries
Tube-Link(Swin-L)
79.4
64.3
47.5
63.6
58.4
Tube-Link: A Flexible Cross Tube Framework for Universal Video Segmentation
DeVIS (Swin-L)
77.7
59.8
43.8
57.8
54.4
DeVIS: Making Deformable Transformers Work for Video Instance Segmentation
MinVIS (Swin-L)
76.6
62
45.9
60.8
55.3
MinVIS: A Minimal Video Instance Segmentation Framework without Video-based Training
BoxVIS(Swin-L & Box-sup)
76.4
59.6
44.8
61.0
53.9
BoxVIS: Video Instance Segmentation with Box Annotations
InstanceFormer (Swin-L)
73.7
56.9
42.8
56.0
51.0
InstanceFormer: An Online Video Instance Segmentation Framework
TarViS (Swin-T)
71.6
56.6
42.2
57.2
50.9
TarViS: A Unified Approach for Target-based Video Segmentation
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Video Instance Segmentation On Youtube Vis 2 | SOTA | HyperAI