KyungMinJin/HANet

Kinematic-aware Hierarchical Attention Network for Human Pose Estimation in Videos (WACV 2023)

25
/ 100
Experimental

This project helps researchers and engineers accurately track human movement in videos. It takes video footage as input and outputs precise 2D and 3D human pose estimations, including body mesh recovery, even with occlusions or rapid motion. This is for computer vision researchers, biomechanists, and animators who need high-quality human motion data.

No commits in the last 6 months.

Use this if you need to analyze detailed human kinematics from video, such as for sports analysis, medical diagnostics, or creating realistic character animations.

Not ideal if you are looking for a plug-and-play application without needing to run experiments or work with machine learning frameworks.

human-motion-tracking biomechanics-analysis animation video-analytics computer-vision-research
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 8 / 25
Maturity 8 / 25
Community 9 / 25

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Stars

54

Forks

4

Language

Python

License

Last pushed

Oct 29, 2023

Commits (30d)

0

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