Deepfake Synthetic-20K Dataset

Citation Author(s):
Sahil
Sharma
Ulster University
Ashima
Sood
Ulster University
Vijay
Kumar
Dr. B R Ambedkar National Institute of Technology
Submitted by:
Sahil Sharma
Last updated:
Mon, 04/15/2024 - 06:14
DOI:
10.21227/67x4-9g14
Data Format:
License:
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Abstract 

The Deepfake-Synthetic-20K dataset significantly contributes to digital forensics and deepfake detection research. It comprises 20,000 high-resolution, synthetic human face images generated using the advanced StyleGAN-2 architecture. This dataset is designed to support the development and evaluation of machine-learning models that can differentiate between real and artificially synthesized human faces. Each image in the dataset has been meticulously crafted to ensure a diverse representation of age, gender, and ethnicity, reflecting the variability seen in global human populations. The images were produced under controlled conditions to mimic the subtleties and complexities of genuine human faces, thereby providing a robust platform for training and testing deepfake detection algorithms. Additionally, the dataset adheres to ethical guidelines, avoiding privacy violations and consent issues associated with using real human images. This dataset is available to academics and researchers under a Creative Commons license, facilitating wide access and collaborative advancements in combating deepfake technology's challenges.

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Submitted by Ankita Sarkar on Thu, 08/01/2024 - 22:40