SDFVD: Small-scale Deepfake Forgery Video Dataset

Published: 23 April 2024| Version 1 | DOI: 10.17632/bcmkfgct2s.1


Small-scale Deepfake Forgery Video Dataset (SDFVD) is a custom dataset consisting of real and deepfake videos with diverse contexts designed to study and benchmark deepfake detection algorithms. The dataset comprising of a total of 106 videos, with 53 original and 53 deepfake videos. Equal number of real and deepfake videos, ensures balance for machine learning model training and evaluation. The original videos were collected from Pexels: a well- known provider of stock photography and stock footage(video). These videos include a variety of backgrounds, and the subjects represent different genders and ages, reflecting a diverse range of scenarios. The input videos have been pre-processed by cropping them to a length of approximately 4 to 5 seconds and resizing them to 720p resolution, ensuring a consistent and uniform format across the dataset. Deepfake videos were generated using Remaker AI employing face-swapping techniques. Remaker AI is an AI-powered platform that can generate images, swap faces in photos and videos, and edit content. The source face photos for these swaps were taken from Freepik: is an image bank website provides contents such as photographs, illustrations and vector images. SDFVD was created due to the lack of availability of any such comparable small-scale deepfake video datasets. Key benefits of such datasets are: • In educational settings or smaller research labs, smaller datasets can be particularly useful as they require fewer resources, allowing students and researchers to conduct experiments with limited budgets and computational resources. • Researchers can use small-scale datasets to quickly prototype new ideas, test concepts, and refine algorithms before scaling up to larger datasets. Overall, SDFVD offers a compact but diverse collection of real and deepfake videos, suitable for a variety of applications, including research, security, and education. It serves as a valuable resource for exploring the rapidly evolving field of deepfake technology and its impact on society.



Akkamahadevi Women's University


Computer Vision, Cybersecurity, Computer Security and Privacy, Biometrics, Computer Forensics, Information Security, Video Processing, Deepfake