---
license: apache-2.0
task_categories:
- object-detection
tags:
- multi-object-tracking
- mot
- pedestrian
- cctv
- person-tracking
pretty_name: CrowdTrack-MOT
---

# CrowdTrack-MOT

![CrowdTrack-MOT sample sequences](assets/header.jpg)

Pedestrian multi-object-tracking benchmark in **MOTChallenge format**, derived from
[Loseevaya/CrowdTrack](https://huggingface.co/datasets/Loseevaya/CrowdTrack).
33 CCTV / surveillance sequences, single class `person`, ~702k GT boxes, 1920×1080.

## What changed vs. the original

1. **Converted to [MOT format](https://docs.cvat.ai/docs/dataset_management/formats/format-mot/)**
   and added a `seqinfo.ini` per sequence. The original ships two heterogeneous
   annotation formats (a few sequences as plain `gt.txt`, the rest as per-frame
   LabelMe JSON) — both are unified into a single MOT `gt.txt`.
   *(`frameRate=25` in `seqinfo.ini` is a hardcoded placeholder — the original FPS
   is unknown.)*
2. **Boxes clipped to the frame.** Some original boxes extended past the image
   border (and a few were stored with inverted/negative width-height); these are
   normalized to top-left + positive size and clipped to the frame bounds.

## Layout

```
train/
  trackNNNN/
    img1/000001.<ext> ...     # frames, 1-indexed MOT naming (.jpg or .png)
    gt/gt.txt                 # frame,id,x,y,w,h,1,1,1   (class: person)
    seqinfo.ini
```

## Download

```bash
hf download Fleyderer/CrowdTrack-MOT --repo-type dataset --local-dir CrowdTrack-MOT
```

Works as a benchmark in [BoxMOT](https://github.com/mikel-brostrom/boxmot):

```bash
boxmot eval --benchmark crowdtrack-mot --detector <det> --reid <reid> --tracker <trk>
```

## Credits

- **Original benchmark:** *CrowdTrack: A Benchmark for Difficult Multiple Pedestrian
  Tracking in Real Scenarios* — Teng Fu, Yuwen Chen, Zhuofan Chen, Mengyang Zhao,
  Bin Li, Xiangyang Xue ([arXiv:2507.02479](https://arxiv.org/abs/2507.02479)).
- **Source data:** [Loseevaya/CrowdTrack](https://huggingface.co/datasets/Loseevaya/CrowdTrack) — all imagery and original annotations.
- **MOT conversion / clipping / packaging:** Fleyderer.

## Citation

If you use this dataset, please cite the original CrowdTrack paper:

```bibtex
@article{fu2025crowdtrack,
  title   = {CrowdTrack: A Benchmark for Difficult Multiple Pedestrian Tracking in Real Scenarios},
  author  = {Fu, Teng and Chen, Yuwen and Chen, Zhuofan and Zhao, Mengyang and Li, Bin and Xue, Xiangyang},
  journal = {arXiv preprint arXiv:2507.02479},
  year    = {2025}
}
```