The Deepfake Detection Challenge (DFDC) Preview Dataset
This dataset addresses the problem of detecting deepfakes for researchers and practitioners, but it is incremental as it builds on existing data collection efforts.
The paper introduces the Deepfake Detection Challenge (DFDC) Preview Dataset, consisting of 5,000 videos with two facial modification algorithms, and defines evaluation metrics while testing two existing models to establish a baseline performance.
In this paper, we introduce a preview of the Deepfakes Detection Challenge (DFDC) dataset consisting of 5K videos featuring two facial modification algorithms. A data collection campaign has been carried out where participating actors have entered into an agreement to the use and manipulation of their likenesses in our creation of the dataset. Diversity in several axes (gender, skin-tone, age, etc.) has been considered and actors recorded videos with arbitrary backgrounds thus bringing visual variability. Finally, a set of specific metrics to evaluate the performance have been defined and two existing models for detecting deepfakes have been tested to provide a reference performance baseline. The DFDC dataset preview can be downloaded at: deepfakedetectionchallenge.ai