Arthur151/ROMP
Monocular, One-stage, Regression of Multiple 3D People and their 3D positions & trajectories in camera & global coordinates. ROMP[ICCV21], BEV[CVPR22], TRACE[CVPR2023] 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: 2203
- days_rel: n/a
- days_push: 657
- n_releases_24m: 0
Adoption not part of the score
1538 stars · 246 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
ROMP is a PyTorch-based library and pip-installable API (simple-romp) for real-time monocular multi-person 3D human mesh recovery, implementing the ROMP (ICCV21), BEV (CVPR22), and TRACE (CVPR23) models. It regresses SMPL body meshes, depth relationships, subject tracking, and global 3D trajectories from single-camera video, with export to fbx/glb/bvh formats.
Use cases
- recover 3d human meshes from a single image or video
- estimate multi-person 3d poses and positions from monocular camera footage
- track specific people across video frames and get their global 3d trajectories
- estimate depth relationships between multiple people in a scene
- export 3d human motion to fbx glb or bvh for animation pipelines
- run real-time 3d pose estimation on gpu or cpu with onnx
- drive blender or game-engine characters from video of people
When to choose
- you need multi-person 3d body mesh recovery from monocular video in real time
- you want SMPL-format outputs with global coordinates and camera tracking
- you need cross-platform (Linux/Windows/Mac) inference via pip with fbx/glb/bvh export
- you want to reproduce or extend published research models (ROMP, BEV, TRACE)
When to avoid
- you need high-accuracy single-person pose with heavy occlusion handling beyond these models' scope
- you require face or hand mesh recovery (SMPL-X style full-body)
- you need a maintained production product - development activity has slowed since 2023-2024
- you work outside Python/PyTorch ecosystems and cannot use the provided API or Docker
Facets
library · maturity stable
computer-vision machine-learning deep-learning image-processing computer-vision machine-learning deep-learning artificial-intelligence windows python 3d-human-pose-estimation smpl multi-person mesh-recovery pytorch human-tracking 3d-trajectory onnx linux macos gpu
2 sources
- readme: https://github.com/Arthur151/ROMP · fetched 2026-08-28 · 29f1996d1dcb
- homepage: https://www.yusun.work/ · fetched 2026-08-29 · 9130fa6ebde3
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| Arthur151/ROMP | main | 23 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem