# xingyizhou/CenterTrack

Simultaneous object detection and tracking using center points.

Repository: https://github.com/xingyizhou/CenterTrack
Canonical: https://ross.abutalabs.com/products/centertrack
Language: Python
License: MIT
License Family: permissive
Last push: 2024-06-17T23:04:07+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2344, "days_push": 807, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2478, forks 515 (observed 2026-08-28T04:06:55.145789+00:00)

## What it is
CenterTrack is a deep learning model and research codebase that performs simultaneous multi-object detection and tracking using center points, as published at ECCV 2020. It supports 2D tracking, monocular 3D tracking, multi-category tracking, and pose tracking, with state-of-the-art results on MOT17, KITTI, and nuScenes benchmarks.

## Use cases
- track pedestrians in video in real time
- detect and track vehicles for autonomous driving research
- run monocular 3D object tracking on nuScenes
- train a tracker on still image datasets without video
- reproduce MOT17 and KITTI tracking benchmark results
- extend tracking to multi-category or pose tracking

## When to choose
- you need an online, real-time joint detection-and-tracking model
- you want a research baseline for multi-object or 3D tracking benchmarks
- you only have static image datasets for training

## When to avoid
- you need a production-ready maintained pipeline rather than research code
- you need offline or batch tracking with future-frame information
- you work outside Python/PyTorch environments

## Facets
- artifact type: library
- maturity: maintenance
- function: computer-vision, machine-learning, deep-learning, image-processing
- domain: computer-vision, machine-learning, autonomous-vehicles
- platform: python
- tags: object-detection, object-tracking, multi-object-tracking, 3d-tracking, centerpoint, research-code, pytorch, linux, gpu

## Member repositories
- xingyizhou/CenterTrack (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:55.145789+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 2026-08-30T02:28:19.058377+00:00, confidence not recorded.
  - readme: https://github.com/xingyizhou/CenterTrack (fetched 2026-08-28T04:06:55.145789+00:00, sha c72ddee8e414)
- Data as of 2026-08-30T08:39:29.467469+00:00.