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Benchmarks
Dive Recognition on MTL-AQA (test)
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96.32
Position Accuracy
C3D-AVG
73.9288
79.7419
85.555
91.3681
Dec 10, 2019
Position Accuracy
Armstand Accuracy
Rotation Type Accuracy
Somersaults Accuracy (SS)
Twists Accuracy (TW)
Updated 4d ago
Evaluation Results
Method
Method
Links
Position Accuracy
Armstand Accuracy
Rotation Type Accuracy
Somersaults Accuracy (SS)
Twists Accuracy (TW)
C3D-AVG
CNN Type=3D, Number of...
2019.12
96.32
99.72
97.45
96.88
93.2
HalluciNet (ResNet-18)
CNN Type=2D, Number of...
2019.12
91.78
99.43
95.47
88.1
89.24
VGG11
CNN Type=2D, Number of...
2019.12
90.08
99.43
92.07
83
86.69
HalluciNet (VGG11)
CNN Type=2D, Number of...
2019.12
89.52
99.43
96.32
86.12
88.1
MSCADC
CNN Type=3D, Number of...
2019.12
78.47
97.45
84.7
76.2
82.72
Nibali et al.
CNN Type=3D, Number of...
2019.12
74.79
98.3
78.75
77.34
79.89
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