Deepfake-Synthetic-20K Dataset

The Deepfake-Synthetic-20K dataset is a significant contribution to the field of digital forensics and deepfake detection research. It consists of 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, ensuring the avoidance of privacy violations and consent issues associated with the use of real human images. This dataset is openly available to academics and researchers under a Creative Commons license, facilitating wide access and collaborative advancements in combating deepfake technology's challenges.