# henry123-boy/SpaTracker

[CVPR 2024 Highlight] Official PyTorch implementation of SpatialTracker: Tracking Any 2D Pixels in 3D Space

Repository: https://github.com/henry123-boy/SpaTracker
Canonical: https://ross.abutalabs.com/products/spatracker
Language: Python
License: NOASSERTION
License Family: other
Last push: 2025-08-08T01:43:26+00:00

## Health v2 (maintenance only)
Score: 41/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 35, release rhythm 35, longevity 63
- inputs: {"age_days": 884, "days_push": 391, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1057, forks 43 (observed 2026-08-28T04:03:24.686507+00:00)

## What it is
SpatialTracker is the official PyTorch implementation of a CVPR 2024 Highlight paper that tracks any 2D pixels in 3D space from RGB or RGBD video. It combines monocular depth estimation with pixel-wise 3D tracking, and a newer SpatialTrackerV2 model jointly produces depth, camera poses, and 3D tracks.

## Use cases
- track pixels in 3d space from a video
- estimate 3d point trajectories from rgb video
- jointly recover depth camera pose and 3d tracks from video
- run dense point tracking on gpu for research
- lift 2d video tracking into 3d using monocular depth
- reproduce cvpr 2024 spatialtracker paper results

## When to choose
- you need research-grade 3D pixel tracking from monocular video
- you want to build on or compare against state-of-the-art 3D tracking methods
- you have a CUDA GPU with ~22GB memory for dense tracking

## When to avoid
- you need a production-ready, licensed product (license is non-standard)
- you lack a CUDA GPU or cannot install heavy PyTorch and depth-estimation dependencies
- you only need simple 2D point tracking without 3D lifting

## Facets
- artifact type: library
- maturity: active
- function: computer-vision, machine-learning, video-processing, image-processing
- domain: computer-vision, machine-learning, deep-learning
- platform: python
- tags: point-tracking, 3d-tracking, pytorch, research-code, cvpr-2024, depth-estimation, inference, video, linux, gpu

## Member repositories
- henry123-boy/SpaTracker (main) score 41

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:24.686507+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 2026-08-30T06:57:58.273224+00:00, confidence not recorded.
  - readme: https://github.com/henry123-boy/SpaTracker (fetched 2026-08-28T04:03:24.686507+00:00, sha b545608d0fbe)
- Data as of 2026-08-30T08:39:29.467469+00:00.