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Models/HRNet-w48

HRNet-w48

Reported on 6 benchmarks across 5 tasks · 2 papers · 2 SOTA

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

Knowledge Base2 results

2D Human Pose EstimationonHuman-Art
AP· 2019-02-25
0.417
best: 0.759 (UniPose)
SOTA
Deep High-Resolution Representation Learning for Human Pose Estimation arXiv:1902.09212
2D Human Pose EstimationonHuman-Art
AP (gt bbox)· 2019-02-25
0.769
best: 0.8 (ViTPose-h)
SOTA
Deep High-Resolution Representation Learning for Human Pose Estimation arXiv:1902.09212

Computer Vision2 results

Pose EstimationonAP-10K
AP· uses extra data· 2022-12-07
73.1
best: 82.4 (ViTPose+-H)
ViTPose++: Vision Transformer for Generic Body Pose Estimation arXiv:2212.04246
Animal Pose EstimationonAP-10K
AP· uses extra data· 2022-12-07
73.1
best: 82.4 (ViTPose+-H)
ViTPose++: Vision Transformer for Generic Body Pose Estimation arXiv:2212.04246

Methodology1 result

3DonAP-10K
AP· uses extra data· 2022-12-07
73.1
best: 82.4 (ViTPose+-H)
ViTPose++: Vision Transformer for Generic Body Pose Estimation arXiv:2212.04246

Audio1 result

1 Image, 2*2 StitchionAP-10K
AP· uses extra data· 2022-12-07
73.1
best: 82.4 (ViTPose+-H)
ViTPose++: Vision Transformer for Generic Body Pose Estimation arXiv:2212.04246