SDFVD2.0: Extension of Small Scale Deep Fake Video Dataset

The SDFVD 2.0 is an augmented extension of the original SDFVD dataset, which originally contained 53 real and 53 fake videos. This new version has been created to enhance the diversity and robustness of the dataset by applying various augmentation techniques like horizontal flip, rotation, shear, brightness and contrast adjustment, additive gaussian noise, downscaling and upscaling to the original videos. These augmentations help simulate a wider range of conditions and variations, making the dataset more suitable for training and evaluating deep learning models for deepfake detection. This process has significantly expanded the dataset resulting in 461 real and 461 forged videos, providing a richer and more varied collection of video data for deepfake detection research and development.
Dataset Structure
The dataset is organized into two main directories: real and fake, each containing the original and augmented videos. Each augmented video file is named following the pattern:
‘__aug_.mp4’
where is either real or fake and ranges from 0 to 7 corresponding to the different augmentation techniques applied.