Deepfake-vs-Real-60K is a large-scale image classification dataset designed to distinguish between deepfake and real facial images. The dataset includes approximately 60,000 high-quality images, comprising 30,000 fake (deepfake) and 30,000 real images, to support the development of robust deepfake detection models.
By providing a well-balanced and diverse collection, Deepfake-vs-Real-60K aims to enhance classification accuracy and improve generalization for… See the full description on the dataset page:
https://huggingface.co/datasets/prithivMLmods/Deepfake-vs-Real-60K.
