GONGJIA0208/Diffpose
[CVPR 2023] DiffPose: Toward More Reliable 3D Pose Estimation
This project helps analyze human movement by converting 2D video footage into detailed 3D skeletal poses. It takes standard video data or 2D pose estimations and outputs precise 3D coordinates for human joints, providing a robust understanding of motion. Researchers and practitioners in fields like biomechanics, animation, or sports science would find this useful for analyzing human actions.
187 stars. No commits in the last 6 months.
Use this if you need to transform 2D video recordings of human movement into accurate and reliable 3D pose data for analysis or simulation.
Not ideal if you are looking for a ready-to-use application with a graphical interface, as this project is a code-based solution for researchers and developers.
Stars
187
Forks
13
Language
Python
License
MIT
Category
Last pushed
Dec 28, 2023
Commits (30d)
0
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