A Deepfake Detection Algorithm Based on Fourier Transform of Biological Signal
Source abstract
Abstract
Deepfake-generated fake faces, commonly utilized in identity-related activities such as political propaganda, celebrity impersonations, evidence forgery, and familiar fraud, pose new societal threats. Although current deepfak... | Find, read and cite all the research you need on Tech Science Press
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Image Processing Techniques and Applications · Anomaly Detection Techniques and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (35)
Show source-provided references
1. A style-based generator architecture for generative adversarial networks
2. Face2Face: Real-time face capture and reenactment of RGB videos
3. Deferred neural rendering: Image synthesis using neural textures10.1145/3306346.3323035 ↗
4. Real-time expression transfer for facial reenactment10.1145/2816795.2818056 ↗
5. White paper: Deep fakery–an action plan
6. Deepfake detection using deep learning methods: A systematic and comprehensive review
7. A novel blockchain-based deepfake detection method using federated and deep learning models
8. FakeCatcher: Detection of synthetic portrait videos using biological signals
9. How do the hearts of deep fakes beat? Deep fake source detection via interpreting residuals with biological signals
10. In ictu oculi: Exposing AI created fake face videos by detecting eye blinking
11. DeepVision: Deepfakes detection using human eye blinking pattern10.1109/ACCESS.2020.2988660 ↗
12. HyperFace: A deep multi-task learning framework for face detection, landmark localization, pose estimation, and gender recognition10.1109/TPAMI.2017.2781233 ↗
13. Real-time eye blink detection using facial landmarks
14. Protecting world leaders against deep fakes
15. Exploiting visual artifacts to expose DeepFakes and face manipulations
16. Exposing deep fakes using inconsistent head poses
17. Exposing DeepFake videos by detecting face warping artifacts
18. Celeb-DF: A large-scale challenging dataset for DeepFake forensics
19. FaceForensics++: Learning to detect manipulated facial images
20. B. Dolhansky, R. Howes, B. Pflaum, N. Baram, and C. C. Ferrer, “The deepfake detection challenge (DFDC) preview dataset,” 2019. doi: 10.48550/arXiv.1910.08854.
21. H. H. Nguyen, J. Yamagishi, and I. Echizen, “Use of a capsule network to detect fake images and videos,” 2019. doi: 10.48550/arXiv.1910.12467.10.1109/ICASSP.2019.8682602 ↗
22. MesoNet: A compact facial video forgery detection network
23. Twostream neural networks for tampered face detection
24. Multi-task learning for detecting and segmenting manipulated facial images and videos
25. On the detection of digital face manipulation
26. Multi-attentional deepfake detection
27. DeepFakes evolution: Analysis of facial regions and fake detection performance
28. DeepRhythm: Exposing DeepFakes with attentional visual heartbeat rhythms
29. DeepFakes detection based on heart rate estimation: Single-and multi-frame
30. Robust pulse rate from chrominance-based rPPG10.1109/TBME.2013.2266196 ↗
31. P. Korshunov and S. Marcel, “DeepFakes: A new threat to face recognition? Assessment and detection,” 2018. doi: 10.48550/arXiv.1812.08685.
32. Multi-region probabilistic histograms for robust and scalable identity inference
33. Twobranch recurrent network for isolating deepfakes in videos
34. Thinking in frequency: Face forgery detection by mining frequency-aware clues
35. Generalizing face forgery detection with high-frequency features