Project Details
Description
Usage of AI techniques to identify whether a video or an image has been artificially manipulated to create realistic but fake content.
Layman's description
Spotting fake videos or images that look real but were created by computers.
| Status | Active |
|---|---|
| Effective start/end date | 6/03/23 → … |
Keywords
- AI
- Machine learning
- Computer vision
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Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
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FlashF5-MaViT: a fast five frequency Mamba with CDC–FastViT architecture for deepfake detection
Badr, N. E. A., Liang, X., Nebel, J.-C. & Greenhill, D., 31 Mar 2026, 2025 9th International Conference on Vision, Image and Signal Processing (ICVISP). Piscataway, U.S.: Institute of Electrical and Electronics Engineers, 8 p. (International Conference on Vision, Image and Signal Processing (ICVISP)).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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WaViT-CDC: wavelet vision transformer with central difference convolutions for spatial-frequency deepfake detection
Badr, N. E. A., Nebel, J. C., Greenhill, D. & Liang, X., 2025, In: IEEE Open Journal of Signal Processing. 6, p. 621-630 10 p.Research output: Contribution to journal › Article › peer-review
Open Access -
A review of deepfake techniques: architecture, detection, and datasets
Edwards, P., Nebel, J. C., Greenhill, D. & Liang, X., 30 Oct 2024, In: IEEE Access. 12, p. 154718-154742Research output: Contribution to journal › Article › peer-review