Keypoint Detection¶
We provide benchmarks of different keypoint detection domain adaptation algorithms on as follows. Those domain adaptation algorithms includes:
RHD->H3D accuracy on ResNet-101¶
Methods |
MCP |
PIP |
DIP |
Fingertip |
Avg |
Source Only |
67.4 |
64.2 |
63.3 |
54.8 |
61.8 |
RegDA |
79.6 |
74.4 |
71.2 |
62.9 |
72.5 |
Oracle |
97.7 |
97.2 |
95.7 |
92.5 |
95.8 |
Surreal->Human3.6M accuracy on ResNet-101¶
Methods |
Shoulder |
Elbow |
Wrist |
Hip |
Knee |
Ankle |
Avg |
Source Only |
69.4 |
75.4 |
66.4 |
37.9 |
77.3 |
77.7 |
67.3 |
RegDA |
73.3 |
86.4 |
72.8 |
54.8 |
82.0 |
84.4 |
75.6 |
Oracle |
95.3 |
91.8 |
86.9 |
95.6 |
94.1 |
93.6 |
92.9 |
Surreal->LSP accuracy on ResNet-101¶
Methods |
Shoulder |
Elbow |
Wrist |
Hip |
Knee |
Ankle |
Avg |
Source Only |
51.5 |
65.0 |
62.9 |
68.0 |
68.7 |
67.4 |
63.9 |
RegDA |
62.7 |
76.7 |
71.1 |
81.0 |
80.3 |
75.3 |
74.6 |
