# ByteTrack Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/bytetrack
> Markdown URL: https://aitinkerers.org/technologies/bytetrack.md
> Technology record last updated: 2026-08-27T06:49:13Z
> Generated: 2026-10-23T02:45:38Z

ByteTrack delivers a simple, effective, and industry-leading solution for multi-object tracking.

ByteTrack redefines multi-object tracking by associating every detection box instead of just the high-score ones. This 'associate-all' strategy, coupled with a high-performance detector like YOLOX, significantly boosts tracking accuracy and reduces identity switches. It achieves state-of-the-art performance across various benchmarks, including MOT17 (77.3 MOTA), MOT20 (71.7 MOTA), and BDD100K. Its efficiency and accuracy make it ideal for real-world applications (e.g., autonomous driving, surveillance), offering a robust and scalable tracking solution.

- Official technology site: https://github.com/ifzhang/ByteTrack
- Public AI Tinkerers demos and talks: 1
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Detection was the easy part: re-identification on real store cameras](https://lahore.aitinkerers.org/talks/rsvp_rjgHdviyAUI)

- Event context: AI Tinkerers Lahore: September 19, 2026 — 2026-09-19 — Lahore
- Public talk page: https://lahore.aitinkerers.org/talks/rsvp_rjgHdviyAUI

## Related Technologies

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- [RF-DETR](https://aitinkerers.org/technologies/rf-detr) ([Markdown](https://aitinkerers.org/technologies/rf-detr.md)) — 2 public demos
- [RTSP](https://aitinkerers.org/technologies/rtsp) ([Markdown](https://aitinkerers.org/technologies/rtsp.md)) — 3 public demos
- [YOLO](https://aitinkerers.org/technologies/yolo) ([Markdown](https://aitinkerers.org/technologies/yolo.md)) — 9 public demos