---
title: "visionml/pytracking: papers citing this GitHub repository"
description: "5 papers in the tracked journals link to the GitHub repository visionml/pytracking in their Crossref records, the first in 2023; most of them (2) in 2023."
url: https://scholar4ai.com/code/github-visionml-pytracking
markdown_url: https://scholar4ai.com/code/github-visionml-pytracking.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "5 papers in the tracked journals link to the GitHub repository visionml/pytracking in their Crossref records, the first in 2023; most of them (2) in 2023. (as of 2026-11-03)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-03T14:43:26+09:00
window: 2026-10-05 to 2026-11-03
source: OpenAlex (CC0)
---

# visionml/pytracking: papers linking to it

Research papers in the 480 tracked journals that link to visionml/pytracking (https://github.com/visionml/pytracking), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

- GitHub
- 3,525 stars
- 613 forks
- Python
- license GPL-3.0
- created 2019
- https://github.com/visionml/pytracking

All repositories: https://scholar4ai.com/code.md

## Key findings

- 5 papers in the tracked journals link to the GitHub repository visionml/pytracking in their Crossref records, the first in 2023; most of them (2) in 2023.
- By category: AI (5); the journals with the most are Pattern Recognition (2), Neural Computing and Applications (1) and Applied Intelligence (1).

## By year

*Papers linking to visionml/pytracking by publication year*

| Year | Papers |
|---|---:|
| 2023 | 2 |
| 2024 | 1 |
| 2025 | 1 |
| 2026 | 1 |

## Journals

*Journals whose papers link to visionml/pytracking most*

| Journal | Papers |
|---|---:|
| [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | 2 |
| [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 1 |
| [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | 1 |
| [Information Fusion](https://scholar4ai.com/journals/information-fusion.md) | 1 |

## Papers

*Papers linking to visionml/pytracking, most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2025-11-08 | [Revisiting color-event based tracking: A unified network, dataset, and metric](https://doi.org/10.1016/j.patcog.2025.112718) | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | Chuanming Tang, Xiao Wang, Ju Huang et al. | 40 | cites it |
| 2024-05-11 | [CRTrack: Learning Correlation-Refine network for visual object tracking](https://doi.org/10.1016/j.patcog.2024.110582) | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | Wenkang Zhang, Fei Xie, Tianyang Xu et al. | 21 | cites it |
| 2023-12-26 | [Self-supervised discriminative model prediction for visual tracking](https://doi.org/10.1007/s00521-023-09348-5) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Di Yuan, Gu Geng, Xiu Shu et al. | 6 | cites it |
| 2026-03-07 | [TSMamba: Multi-drone feature interaction via temporal-spatial mamba networks for aerial object tracking](https://doi.org/10.1016/j.inffus.2026.104279) | [Information Fusion](https://scholar4ai.com/journals/information-fusion.md) | Han Wu, Hao Sun, Kui Liu et al. | 6 | cites it |
| 2023-04-25 | [Multi-template global re-detection based on Gumbel-Softmax in long-term visual tracking](https://doi.org/10.1007/s10489-023-04584-7) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Zhiqiang Hou, Jingyuan Ma, Wangsheng Yu et al. | 3 | cites it |

## How this is measured

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

## Cite this page

Scholar4AI. (2026). visionml/pytracking: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-visionml-pytracking

```bibtex
@misc{scholar4ai-code-github-visionml-pytracking,
  author = {{Scholar4AI}},
  title = {visionml/pytracking: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-visionml-pytracking}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).