mkocabas/EpipolarPose
Self-Supervised Learning of 3D Human Pose using Multi-view Geometry (CVPR2019)
This project helps researchers and practitioners in fields like motion analysis or animation by accurately estimating 3D human poses from standard RGB images or video. It takes a single image of a person as input and outputs a precise 3D model of their pose, without needing special 3D sensing equipment or complex camera setups for training. This tool is ideal for scientists studying human movement or developers creating realistic character animations.
609 stars. No commits in the last 6 months.
Use this if you need to determine a person's 3D body posture from standard 2D video footage or still images, especially when 3D ground-truth data or camera calibration is unavailable.
Not ideal if your primary need is 2D pose detection, or if you require real-time performance on resource-constrained devices without dedicated GPUs.
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Jun 26, 2019
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