Deepfake Images Dataset for GAN vs Real Classification

A collection of images intended for distinguishing between real photographs and synthetic images generated by Generative Adversarial Networks (GANs). The dataset is hosted on Kaggle, but its size, creation date, and author are unknown. Columns and specific file formats are not detailed in the provided metadata.

Use Cases

• Training binary classifiers to distinguish GAN-generated images from real ones (inferred from domain, verify after download)
• Benchmarking the performance of deepfake detection algorithms (inferred from domain, verify after download)
• Studying the visual artifacts and failure modes of generative models (inferred from domain, verify after download)

Strengths

• Published on Kaggle, a platform with established data sharing and versioning tools.

Limitations

• Metadata is minimal; actual content requires verification after download.
• Row count, file formats, and column definitions are unknown, which may limit suitability assessment.
• License and authorship are unknown, complicating usage rights evaluation.

Provenance

Source

Kaggle