12 datasets found

Deepfakes are synthetically generated images, videos or audios, which fraudsters use to manipulate legitimate information. The proposed technique outperforms state-of-the-art...

The ASVspoof 2019 LA dataset is comprised of bonafide and spoofed utterances generated using totally 19 different spoofing algorithms, including TTS, VC, and replay attacks.

A challenging real-world dataset for deepfake detection.

A deepfake detection method that can address the issue of modifying segments of videos using generative techniques.

DeepfakeTIMIT dataset consists of 5,639 deepfake videos and 890 real videos.

Deepfake video detection using Generative Convolutional Vision Transformer (GenConViT) for deepfake video detection. Our model combines ConvNeXt and Swin Transformer models for...

Face forgery by deepfake is widely spread over the internet and has raised severe societal concerns. Recently, how to detect such forgery contents has become a hot research...

A dedicated collection of images: real/pristine images collected from CelebA, FFHQ1, and ImageNet datasets and synthetic data generated by 9 different Generative Adversarial...

The Diffusion Forensics (DFo) dataset is a large-scale dataset for diffusion-generated image detection, containing 60,000 images.

The Deep Fake Detection Competition (DFDC) dataset is a large-scale dataset for deepfake detection, containing 124,000 videos.

DeeperForensics-1.0 is a large-scale dataset for real-world face forgery detection, containing 60,000 videos and 17.6 million frames.

Deepfakes have become a critical social problem, and detecting them is of utmost importance. The FaceForensics++ dataset offers fake video datasets. Most of the detection...