# zju3dv/EasyMocap

Make human motion capture easier.

Repository: https://github.com/zju3dv/EasyMocap
Canonical: https://ross.abutalabs.com/products/easymocap
Language: Python
License: NOASSERTION
License Family: other
Topics: motion-capture
Last push: 2026-03-01T11:35:26+00:00

## Health v2 (maintenance only)
Score: 54/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 70, release rhythm 8, longevity 100
- inputs: {"age_days": 2057, "days_push": 185, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 4783, forks 560 (observed 2026-08-28T04:08:59.667745+00:00)

## What it is
EasyMocap is an open-source Python toolbox for markerless human motion capture and novel view synthesis from RGB videos. It fits parametric body models like SMPL, SMPL-X, and MANO using single-view internet videos or calibrated multi-view camera setups.

## Use cases
- capture 3d human motion from multiple synchronized rgb cameras
- fit smpl or smpl-x body models to 2d keypoints from video
- reconstruct body hand and face poses without markers or suits
- estimate human motion from a single internet video
- recover 3d pose from a video of a person in front of a mirror
- generate novel views of a human from sparse multi-view videos
- build a motion capture dataset for animation or research

## When to choose
- you need markerless motion capture from rgb video without wearable sensors
- you have calibrated multi-view cameras and want high-quality smpl fits
- you want to extract 3d human pose from ordinary youtube or single-camera footage
- you are doing computer vision research on human body reconstruction or novel view synthesis

## When to avoid
- you need real-time mocap for live performance or games
- you require marker-based precision comparable to commercial optical mocap systems
- you want a polished gui application rather than python scripts and research code
- your input is depth sensors or imu data rather than rgb video

## Facets
- artifact type: library
- maturity: active
- function: computer-vision, machine-learning, image-processing, video-processing
- domain: computer-vision, machine-learning, graphics
- platform: python, cross-platform
- tags: motion-capture, markerless-mocap, smpl, human-pose-estimation, novel-view-synthesis, multi-view, 3d-human-reconstruction, linux

## Member repositories
- zju3dv/EasyMocap (main) score 54

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:59.667745+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:18:43.373487+00:00, confidence not recorded.
  - readme: https://github.com/zju3dv/EasyMocap (fetched 2026-08-28T04:08:59.667745+00:00, sha 6936f718cef9)
- Data as of 2026-08-30T08:39:29.467469+00:00.