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Models/MIPNet

MIPNet

Reported on 18 benchmarks across 3 tasks · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision6 results

Pose EstimationonCOCO test-dev
AP· 2021-01-27
75.7
best: 81.1 (ViTPose (ViTAE-G, ensemble))
Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation arXiv:2101.11223
Pose EstimationonCOCO test-dev
AP50· 2021-01-27
92.4
best: 95 (ViTPose (ViTAE-G, ensemble))
Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation arXiv:2101.11223
Pose EstimationonCOCO test-dev
AP75· 2021-01-27
83.3
best: 88.2 (ViTPose (ViTAE-G, ensemble))
Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation arXiv:2101.11223
Pose EstimationonCOCO test-dev
APL· 2021-01-27
81.2
best: 86.5 (PoseBH-H)
Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation arXiv:2101.11223
Pose EstimationonCOCO test-dev
APM· 2021-01-27
71.4
best: 83.8 (4xRSN-50 (ensemble))
Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation arXiv:2101.11223
Pose EstimationonCOCO test-dev
AR· 2021-01-27
80.5
best: 88.2 (Simple Pose)
Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation arXiv:2101.11223

Methodology6 results

3DonCOCO test-dev
AP· 2021-01-27
75.7
best: 81.1 (ViTPose (ViTAE-G, ensemble))
Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation arXiv:2101.11223
3DonCOCO test-dev
AP50· 2021-01-27
92.4
best: 95 (ViTPose (ViTAE-G, ensemble))
Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation arXiv:2101.11223
3DonCOCO test-dev
AP75· 2021-01-27
83.3
best: 88.2 (ViTPose (ViTAE-G, ensemble))
Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation arXiv:2101.11223
3DonCOCO test-dev
APL· 2021-01-27
81.2
best: 86.5 (PoseBH-H)
Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation arXiv:2101.11223
3DonCOCO test-dev
APM· 2021-01-27
71.4
best: 83.8 (4xRSN-50 (ensemble))
Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation arXiv:2101.11223
3DonCOCO test-dev
AR· 2021-01-27
80.5
best: 88.2 (Simple Pose)
Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation arXiv:2101.11223

Audio6 results

1 Image, 2*2 StitchionCOCO test-dev
AP· 2021-01-27
75.7
best: 81.1 (ViTPose (ViTAE-G, ensemble))
Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation arXiv:2101.11223
1 Image, 2*2 StitchionCOCO test-dev
AP50· 2021-01-27
92.4
best: 95 (ViTPose (ViTAE-G, ensemble))
Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation arXiv:2101.11223
1 Image, 2*2 StitchionCOCO test-dev
AP75· 2021-01-27
83.3
best: 88.2 (ViTPose (ViTAE-G, ensemble))
Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation arXiv:2101.11223
1 Image, 2*2 StitchionCOCO test-dev
APL· 2021-01-27
81.2
best: 86.5 (PoseBH-H)
Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation arXiv:2101.11223
1 Image, 2*2 StitchionCOCO test-dev
APM· 2021-01-27
71.4
best: 83.8 (4xRSN-50 (ensemble))
Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation arXiv:2101.11223
1 Image, 2*2 StitchionCOCO test-dev
AR· 2021-01-27
80.5
best: 88.2 (Simple Pose)
Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation arXiv:2101.11223