---
title: "iperov/DeepFaceLab: papers citing this GitHub repository"
description: "8 papers in the tracked journals link to the GitHub repository iperov/DeepFaceLab in their Crossref records, the first in 2021; most of them (3) in 2022."
url: https://scholar4ai.com/code/github-iperov-deepfacelab
markdown_url: https://scholar4ai.com/code/github-iperov-deepfacelab.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "8 papers in the tracked journals link to the GitHub repository iperov/DeepFaceLab in their Crossref records, the first in 2021; most of them (3) in 2022. (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)
---

# iperov/DeepFaceLab: papers linking to it

Research papers in the 480 tracked journals that link to iperov/DeepFaceLab (https://github.com/iperov/DeepFaceLab), 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
- 19,274 stars
- 965 forks
- Python
- license GPL-3.0
- created 2018
- archived
- https://github.com/iperov/DeepFaceLab

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

## Key findings

- 8 papers in the tracked journals link to the GitHub repository iperov/DeepFaceLab in their Crossref records, the first in 2021; most of them (3) in 2022.
- By category: AI (7) and Information Systems (1); the journals with the most are Expert Systems with Applications (2), Applied Intelligence (2) and International Journal of Information Management Data Insights (1).
- 3 of the papers build on one another: a later paper cites an earlier one that also links iperov/DeepFaceLab.

## By year

*Papers linking to iperov/DeepFaceLab by publication year*

| Year | Papers |
|---|---:|
| 2021 | 1 |
| 2022 | 3 |
| 2023 | 2 |
| 2024 | 1 |
| 2025 | 1 |

## Journals

*Journals whose papers link to iperov/DeepFaceLab most*

| Journal | Papers |
|---|---:|
| [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 2 |
| [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | 2 |
| [International Journal of Information Management Data Insights](https://scholar4ai.com/journals/international-journal-of-information-management-data-insights.md) | 1 |
| [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 1 |
| [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | 1 |

## Family tree

Each paper sits under the earlier paper it builds on.

- [Deepfakes generation and detection: state-of-the-art, open challenges, countermeasures, and way forward](https://doi.org/10.1007/s10489-022-03766-z) (Applied Intelligence, 2022)
  - [An integrated spatiotemporal-based methodology for deepfake detection](https://doi.org/10.1007/s00521-022-07633-3) (Neural Computing and Applications, 2022) — cites the paper above
  - [TAN-GFD: generalizing face forgery detection based on texture information and adaptive noise mining](https://doi.org/10.1007/s10489-023-04462-2) (Applied Intelligence, 2023) — cites the paper above

## Papers

*Papers linking to iperov/DeepFaceLab, most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2022-06-03 | [Deepfakes generation and detection: state-of-the-art, open challenges, countermeasures, and way forward](https://doi.org/10.1007/s10489-022-03766-z) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Momina Masood, Marriam Nawaz, Khalid Mahmood Malik et al. | 545 | cites it |
| 2021-12-22 | [Exposing deepfakes using a deep multilayer perceptron – convolutional neural network model](https://doi.org/10.1016/j.jjimei.2021.100054) | [International Journal of Information Management Data Insights](https://scholar4ai.com/journals/international-journal-of-information-management-data-insights.md) | Santosh Kolagati, T. Chindrella Priyadharshini, V. Mary Anita Rajam | 88 | cites it |
| 2022-08-02 | [An integrated spatiotemporal-based methodology for deepfake detection](https://doi.org/10.1007/s00521-022-07633-3) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Aya Ismail, Marwa S. Elpeltagy, Mervat S. Zaki et al. | 42 | cites it |
| 2022-11-13 | [Watching the BiG artifacts: Exposing DeepFake videos via Bi-granularity artifacts](https://doi.org/10.1016/j.patcog.2022.109179) | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | Han Chen, Yuezun Li, Dongdong Lin et al. | 39 | cites it |
| 2023-06-28 | [MRT-Net: Auto-adaptive weighting of manipulation residuals and texture clues for face manipulation detection](https://doi.org/10.1016/j.eswa.2023.120898) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Ankit Kumar Yadav, Dinesh Kumar Vishwakarma | 34 | cites it |
| 2023-02-16 | [TAN-GFD: generalizing face forgery detection based on texture information and adaptive noise mining](https://doi.org/10.1007/s10489-023-04462-2) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Yi Xiao Zhao, Xin Jin, Song Gao et al. | 29 | cites it |
| 2024-08-12 | [Rethinking Open-World DeepFake Attribution with Multi-perspective Sensory Learning](https://doi.org/10.1007/s11263-024-02184-7) | [International Journal of Computer Vision](https://scholar4ai.com/journals/international-journal-of-computer-vision.md) | Zhimin Sun, Shen Chen, Taiping Yao et al. | 12 | cites it |
| 2025-06-14 | [FAME: a lightweight spatio-temporal network for model attribution of face-swap deepfakes](https://doi.org/10.1016/j.eswa.2025.128571) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Wasim Ahmad, Yan‐Tsung Peng, Yuan-Hao Chang | 10 | 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). iperov/DeepFaceLab: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-iperov-deepfacelab

```bibtex
@misc{scholar4ai-code-github-iperov-deepfacelab,
  author = {{Scholar4AI}},
  title = {iperov/DeepFaceLab: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-iperov-deepfacelab}},
  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/).