jeffffffli/HybrIK
Official code of "HybrIK: A Hybrid Analytical-Neural Inverse Kinematics Solution for 3D Human Pose and Shape Estimation", CVPR 2021 observed · 2026-08-28
Health v2 · maintenance only
23/100
- Activity 0
- Release rhythm 8
- Longevity 100
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 2102
- days_rel: n/a
- days_push: 602
- n_releases_24m: 0
Adoption not part of the score
1618 stars · 190 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
HybrIK is the official PyTorch implementation of a hybrid analytical-neural inverse kinematics method for 3D human pose and shape estimation from images. It recovers SMPL body meshes (and whole-body meshes in HybrIK-X) and includes pretrained models, training code, demos, and a Blender add-on.
Use cases
- estimate 3d human pose and shape from a single image
- recover smpl body mesh from photos or video
- run whole-body mesh recovery including hands and face
- reconstruct human motion for animation in blender
- benchmark 3d pose estimation on datasets like agora
When to avoid
- you need real-time pose estimation on edge devices with limited compute
- you only need simple 2d keypoint detection without body shape
- you require a production-ready api rather than research code
Facets
library · maturity stable
machine-learning computer-vision image-processing computer-vision machine-learning deep-learning python 3d-pose-estimation inverse-kinematics smpl human-mesh-recovery pytorch cvpr body-mesh linux gpu
1 source
- readme: https://github.com/jeffffffli/HybrIK · fetched 2026-08-28 · 5bc213d3b80b
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| jeffffffli/HybrIK | main | 23 |
For agents
markdown · JSON · MCP: product_card(name="jeffffffli/HybrIK")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem