Datasets:

deepsafe
/

wild-test-dataset

license: other
license_name: mixed-upstream
task_categories:
  - video-classification
  - audio-classification
tags:
  - deepfake-detection
  - out-of-distribution
extra_gated_prompt: >-
  This dataset aggregates media from third-party sources under differing terms,
  and contains recordings of real people. Accepting here does not relieve you of
  complying with each upstream source's own licence.
extra_gated_fields:
  I will use this dataset for non-commercial research only: checkbox
  I will comply with each upstream source's own licence: checkbox

DeepSafe Wild Test Set

A held-out set used to check DeepSafe against media it was never tuned on.

What is in it

Source	Files	Type
DeepAction v1	1,966	AI-generated video across several generators
Gary Stafford audio	1,011	synthetic and real speech
Defactify	17	mixed

Why it is separate

The main evaluation dataset trained the ensemble meta-learners. Measuring on it alone would report in-distribution performance and overstate what the detectors do in the wild. This set exists to be the part nothing was fitted to.

The gap between the two is the finding: across 411 generators the ensemble catches 66% of fakes overall, and only 7% of Sora video. Full results in BENCHMARK.md.

Takedown

If you hold rights to any included material, open an issue at https://github.com/deepsafehq/deepsafe-bench. Removal within 48 hours.