Deepfake: An Overview
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Current deepfake training datasets predominantly contain faces of public figures and celebrities, which may not adequately represent the diversity of faces seen in the real world.
“Current datasets predominantly contain faces of public figures and celebrities, which may not adequately represent the diversity of faces seen in the real world.”
From Deepfake forensics: a survey of digital forensic methods for multimodal deepfake identification on social media (2024) · cites this paper as Chadha et al., 2021
Cites
Hinton, G. E., Krizhevsky, A., & Wang, S. D. (2011) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-21735-7_6 · Cited by 1,360 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Audio Deepfake Detection: What Has Been Achieved and What Lies Ahead
Zhang, B., Cui, H., Nguyen, V., & Whitty, M. (2025) · Sensors · doi:10.3390/s25071989 · Cited by 72 · see citing works
Qureshi, S. M., Saeed, A., Almotiri, S. H., Ahmad, F., & Al Ghamdi, M. A. (2024) · PeerJ Computer Science · doi:10.7717/peerj-cs.2037 · Cited by 71 · see citing works
Human performance in detecting deepfakes: A systematic review and meta-analysis of 56 papers
Diel, A., Lalgi, T., Schröter, I. C., MacDorman, K. F., Teufel, M., & Bäuerle, A. (2024) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2024.100538 · Cited by 64 · see citing works
- Authors
- Chadha, A., Kumar, V., Kashyap, S., & Gupta, M.
- Affiliations
- Manav Rachna International Institute of Research and Studies (IN)
- Corresponding author
- Chadha, Anupama
- Venue
- Lecture Notes in Networks and Systems
- Publisher
- Springer Singapore
- Published
- 2021
- Pages
- 557-566
- ISSN
- 2367-3370 (ISSN-L)
- 2367-3389
- OpenAlex
- W3164861235
- Cited by
- 91
- References
- 1
- Citations by year
- 2026: 17 · 2025: 40 · 2024: 21 · 2023: 10 · 2022: 3
- FWCI
- 12.33
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Lecture notes in networks and systems (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Digital Media Forensic Detection
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Generative Adversarial Networks and Image Synthesis
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Keywords
- deepfakes, face swapping, deepfake detection, deepfake generation, synthetic media, privacy risks, security threats, voice manipulation, facial expression manipulation, deep learning
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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