MarekKowalski/FaceSwap: papers linking to it

GitHub · 757 stars · 207 forks · Python · license MIT · created 2016 · github.com/MarekKowalski/FaceSwap

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Research papers in the 480 tracked journals that link to MarekKowalski/FaceSwap (https://github.com/MarekKowalski/FaceSwap), 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.

Key findings#

20 papers in the tracked journals link to the GitHub repository MarekKowalski/FaceSwap in their Crossref records, the first in 2021; most of them (5) in 2024.
By category: AI (20); the journals with the most are International Journal of Computer Vision (5), Expert Systems with Applications (3) and Applied Intelligence (3).
11 of the papers build on one another: a later paper cites an earlier one that also links MarekKowalski/FaceSwap.

By year#

20212026

Papers linking to MarekKowalski/FaceSwap by publication year
Year	Papers
2021	1
2022	4
2023	3
2024	5
2025	3
2026	4

Journals#

Journals whose papers link to MarekKowalski/FaceSwap most
Journal	Papers
International Journal of Computer Vision	5
Expert Systems with Applications	3
Applied Intelligence	3
Pattern Recognition	3
Neural Computing and Applications	2

Family tree#

Each paper sits under the earlier paper it builds on; papers that cite no other paper here start a branch of their own.

PRRNet: Pixel-Region relation network for face forgery detection Pattern Recognition, 2021
- Learning a deep dual-level network for robust DeepFake detection Pattern Recognition, 2022 — cites the paper above
- MRT-Net: Auto-adaptive weighting of manipulation residuals and texture clues for face manipulation detection Expert Systems with Applications, 2023 — cites the paper above
  - FreqFaceNet: an enhanced transformer architecture with dual-order frequency attention for deepfake detection Applied Intelligence, 2025 — cites the paper above
IR-Capsule: Two-Stream Network for Face Forgery Detection Cognitive Computation, 2022
- Dual-Branch Pre-activation Bottleneck Transformer for Face Forgery Detection Cognitive Computation, 2025 — cites the paper above
  - CAPMamba: A hybrid vision model for enhancing generalization in deepfake detection Expert Systems with Applications, 2025 — cites the paper above
Deepfakes generation and detection: state-of-the-art, open challenges, countermeasures, and way forward Applied Intelligence, 2022
- TAN-GFD: generalizing face forgery detection based on texture information and adaptive noise mining Applied Intelligence, 2023 — cites the paper above
Wavelet-packets for deepfake image analysis and detection Machine Learning, 2022
- Rethinking Open-World DeepFake Attribution with Multi-perspective Sensory Learning International Journal of Computer Vision, 2024 — cites the paper above

Papers linking to MarekKowalski/FaceSwap, 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	Applied Intelligence	Momina Masood, Marriam Nawaz, Khalid Mahmood Malik et al.	545	cites it
2021-03-24	PRRNet: Pixel-Region relation network for face forgery detection	Pattern Recognition	Zhihua Shang, Hongtao Xie, Zheng-Jun Zha et al.	107	cites it
2022-08-31	Wavelet-packets for deepfake image analysis and detection	Machine Learning	Moritz Wolter, Felix Blanke, Raoul Heese et al.	69	cites it
2022-06-03	Learning a deep dual-level network for robust DeepFake detection	Pattern Recognition	Wenbo Pu, Jing Hu, Xin Wang et al.	67	cites it
2023-11-23	An ensemble of CNNs with self-attention mechanism for DeepFake video detection	Neural Computing and Applications	Karima Omar, Rasha Hassan Sakr, Mohammed F. Alrahmawy	55	cites it
2024-05-23	WATCHER: Wavelet-Guided Texture-Content Hierarchical Relation Learning for Deepfake Detection	International Journal of Computer Vision	Yuan Wang, Chen Chen, Ning Zhang et al.	37	cites it
2024-06-24	Learning Spatiotemporal Inconsistency via Thumbnail Layout for Face Deepfake Detection	International Journal of Computer Vision	Yuting Xu, Jian Liang, Lijun Sheng et al.	36	cites it
2023-06-28	MRT-Net: Auto-adaptive weighting of manipulation residuals and texture clues for face manipulation detection	Expert Systems with Applications	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	Applied Intelligence	Yi Xiao Zhao, Xin Jin, Song Gao et al.	29	cites it
2022-06-02	IR-Capsule: Two-Stream Network for Face Forgery Detection	Cognitive Computation	Kaihan Lin, Weihong Han, Shudong Li et al.	15	cites it
2024-08-12	Rethinking Open-World DeepFake Attribution with Multi-perspective Sensory Learning	International Journal of Computer Vision	Zhimin Sun, Shen Chen, Taiping Yao et al.	12	cites it
2025-02-25	FreqFaceNet: an enhanced transformer architecture with dual-order frequency attention for deepfake detection	Applied Intelligence	Varun Gupta, Vaibhav Srivastava, Ankit Kumar Yadav et al.	9	cites it
2024-08-13	Test-time Forgery Detection with Spatial-Frequency Prompt Learning	International Journal of Computer Vision	Junxian Duan, Yuang Ai, Jipeng Liu et al.	8	cites it
2026-04-23	Towards few-shot deepfake detection with an enhanced CLIP model	Neural Networks	Yumin Yang, Xueyi Zhang, Bo Yan et al.	5	cites it
2025-06-01	Dual-Branch Pre-activation Bottleneck Transformer for Face Forgery Detection	Cognitive Computation	Kaihan Lin, Jujian Lv, Huimin Zhao et al.	3	cites it
2026-01-29	UniAttack: Unified Physical-Digital Face Attack Detection	International Journal of Computer Vision	Shunxin Chen, Ajian Liu, Hao Fang et al.	2	cites it
2026-04-03	Refining forgery-aware prompts for deepfake detection with pattern blended samples	Pattern Recognition	Caibo Feng, Chunxiao Liu	2	cites it
2024-11-29	Learning dual aggregate features for face forgery detection	Neural Computing and Applications	Yuru Kou, Qian Jiang, Jun Zhang et al.	1	cites it
2025-12-21	CAPMamba: A hybrid vision model for enhancing generalization in deepfake detection	Expert Systems with Applications	Shudong Li, Yilin Feng, Xiaobo Wu et al.	1	cites it
2026-04-23	STCDePhysio : A decoupled deepfake detection framework based on spatio-temporal consistency of human physiological signals	Expert Systems with Applications	Jue Tian, Le Zhang, Yang Liu et al.	0	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). MarekKowalski/FaceSwap: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-marekkowalski-faceswap

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

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