deepfake-detection-challenge: papers linking to it

Kaggle · www.kaggle.com/competitions/deepfake-detection-challenge

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to deepfake-detection-challenge (https://www.kaggle.com/competitions/deepfake-detection-challenge), 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#

3 papers in the tracked journals link to the Kaggle dataset deepfake-detection-challenge in their Crossref records, the first in 2023; most of them (1) in 2026.
By category: AI (3); the journals with the most are Applied Intelligence (2) and Cognitive Computation (1).

By year#

20232026

Papers linking to deepfake-detection-challenge by publication year
Year	Papers
2023	1
2025	1
2026	1

Journals#

Journals whose papers link to deepfake-detection-challenge most
Journal	Papers
Applied Intelligence	2
Cognitive Computation	1

Papers linking to deepfake-detection-challenge, most cited first
Published	Title	Journal	Authors	Citations	Link
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
2025-06-01	A Novel Multi-modality Deepfake Detection Using Cross-Model Fusion–Based Hybrid Harris Whale Depth-Wise Separable Dense Convolutional Bi-GRU Deepfake Model	Cognitive Computation	Talari Venkata Krishna Moorthy, Y. Narasimha Reddy, C. Venkataiah et al.	5	cites it
2026-09-01	Light-wDEF: lightweight deepfake evaluation framework for efficient and reliable visual detection	Applied Intelligence	Muhammad Yousaf, Sarwar Shah Khan, Babar Shah 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). deepfake-detection-challenge: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/kaggle-competition-deepfake-detection-challenge

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

Free to reuse for non-commercial purposes with attribution (CC BY-NC 4.0).