Learning the Manifold of Authenticity: Hybrid-Curvature Representation Learning for Generalizable Deepfake Detection
The practical utility of deepfake detectors is crippled by a crisis of generalization: models that perform well on known manipulation techniques consistently fail when faced with unseen forgeries. We argue this failure stems from a fundamental geometric mismatch. Existing methods implicitly assume t...
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| Główni autorzy: | , , , |
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| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
IEEE
2026-01-01
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| Seria: | IEEE Access |
| Hasła przedmiotowe: | |
| Dostęp online: | https://ieeexplore.ieee.org/document/11557307/ |
| Etykiety: |
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