tianzhi0549/FCOS
FCOS: Fully Convolutional One-Stage Object Detection (ICCV'19) observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases no_license
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: 2702
- days_rel: n/a
- days_push: 998
- n_releases_24m: 0
Adoption not part of the score
3345 stars · 621 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
Official PyTorch implementation of FCOS, a fully convolutional one-stage, anchor-free object detector published at ICCV 2019. It provides training and inference code with pretrained COCO models, ONNX export scripts, and real-time variants.
Use cases
- train an anchor-free object detection model on COCO
- run object detection inference on images with a pretrained FCOS model
- compare anchor-free vs anchor-based detector performance
- export an object detection model to ONNX
- build a real-time object detector with high FPS
- reproduce ICCV 2019 object detection paper results
When to choose
- you need a simple, anchor-free one-stage detector with strong COCO accuracy
- you want a PyTorch research codebase for object detection experiments
- you need fast training and inference compared to Faster R-CNN
When to avoid
- you need a production-supported detector with active maintenance or a permissive license
- you want the latest detection architectures or a maintained framework - prefer Detectron2/AdelaiDet or mmdetection which include FCOS
- you need multi-task vision models beyond detection
Facets
library · maturity maintenance
computer-vision machine-learning deep-learning computer-vision deep-learning python object-detection anchor-free one-stage-detector pytorch coco research-code iccv2019 gpu linux
6 sources
- readme: https://github.com/tianzhi0549/FCOS · fetched 2026-08-28 · f9f49c0cc42b
- homepage: https://arxiv.org/abs/1904.01355 · fetched 2026-08-29 · 1a6876988d97
- site_page: https://info.arxiv.org/about/donate.html · fetched 2026-08-29 · cca9c3a11c56
- site_page: https://info.arxiv.org/about/ourmembers.html · fetched 2026-08-29 · 47cbc55ff1de
- site_page: https://info.arxiv.org/about · fetched 2026-08-29 · a1f16f915a9a
- site_page: https://info.arxiv.org/labs/index.html · fetched 2026-08-29 · b14a8d05a0ec
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| tianzhi0549/FCOS | main | 32 |
For agents
markdown · JSON · MCP: product_card(name="tianzhi0549/FCOS")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem