# xingyizhou/CenterNet

Object detection, 3D detection, and pose estimation using center point detection:

Repository: https://github.com/xingyizhou/CenterNet
Canonical: https://ross.abutalabs.com/products/centernet
Language: Python
License: MIT
License Family: permissive
Last push: 2023-03-02T14:23:04+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": 2696, "days_push": 1280, "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 7573, forks 1934 (observed 2026-08-28T04:10:01.715787+00:00)

## What it is
CenterNet is a PyTorch implementation of the 'Objects as Points' detector, which models objects as single center points detected via keypoint estimation, regressing size, 3D location, orientation, and pose. It supports object detection on COCO, 3D bounding box detection on KITTI, and multi-person pose estimation in a single end-to-end network without NMS.

## Use cases
- detect objects in images in real time
- estimate 3D bounding boxes from monocular images
- run multi-person human pose estimation
- train a fast anchor-free object detector on custom datasets
- benchmark speed-accuracy trade-offs on COCO

## When to choose
- you need a simple, fast, anchor-free detector without NMS post-processing
- you want one framework covering 2D detection, 3D detection, and pose estimation
- you need real-time inference on a GPU

## When to avoid
- you need actively maintained code with recent framework compatibility
- you require state-of-the-art transformer-based detectors like DETR variants
- you need Lidar-based 3D detection (see CenterPoint instead)

## Facets
- artifact type: library
- maturity: maintenance
- function: computer-vision, image-processing, machine-learning, deep-learning
- domain: computer-vision, deep-learning
- platform: python
- tags: object-detection, centernet, keypoint-estimation, 3d-detection, pose-estimation, pytorch, research-code, linux, gpu

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

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:01.715787+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 2026-08-29T17:37:05.162138+00:00, confidence not recorded.
  - readme: https://github.com/xingyizhou/CenterNet (fetched 2026-08-28T04:10:01.715787+00:00, sha 255bf7070157)
- Data as of 2026-08-30T08:39:29.467469+00:00.