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Commercial
DeepFake Videos Dataset
The deepfake dataset contains real and AI-generated deepfake videos, featuring diverse subjects with detailed metadata on age, gender, and ethnicity to help train powerful deepfake detectors
-
- files
- 5,000
-
- people
- 5,000
- Facial Recognition
- Computer Vision
- Machine learning
- Data generation
- Security
- Facial Recognition
- Computer Vision
- Machine learning
- Data generation
- Security
The deepfake dataset contains real and AI-generated deepfake videos, featuring diverse subjects with detailed metadata on age, gender, and ethnicity to help train powerful deepfake detectors
- Facial Recognition
- Computer Vision
- Machine learning
- Data generation
- Security
-
- files
- 5,000
-
- people
- 5,000
Dataset Info
| Characteristic | Data |
| Description | Real video of people with AI-generated faces, where individuals turn their heads in different directions |
| Data types | Video |
| Tasks | Facial recognition, Computer Vision |
| Total number of files | 5,000 |
| Number of people | 5,000 |
| Video generation sites | aisaver.io, faceswapvideo.ai, magichour.ai |
| Labeling | Metadata (age, gender, ethnicity) |
| Gender | Male, Female |
| Ethnicity | Asian (30%), African (70%) |
| Age | Min = 18, max = 80, mean = 45 |
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Statistics
- Distribution by age
- Duration of the video duration
- Distribution by gender
- Distribution by ethnicity
Before You Buy The Full Set
This dataset is available for AI stress testing. We run your model on it and report error rates per class, segment & condition, so you buy only the 5–30% that fixes the classes it missed.
Show me what fails
Technical
Characteristics
| Characteristic | Data |
| Video extension | mp4, MOV |
| Video Resolutions | 1920 x 1080p, 480 x 360p, 1280 x 720p, 720 x 480p, 640 x 480p, 1920 x 920p |
| Video duration | Mean = 9, median = 9, min = 2, max = 34 |
| Frames per second | Mean = 26.6 |
| Devices | iPhone 13 (30%), Google Pixel (70%) |
Dataset Use Cases
FAQs
How large is DeepFake Videos Dataset compared to other available datasets?
With 5,000 video clips and diverse demographic coverage, this collection is one of the largest datasets of its kind. Its scale allows models trained on it to achieve higher accuracy in deepfake content detection and facial recognition tasks.
What devices and resolutions are represented in the dataset?
Videos were recorded on iPhone 13 devices (30%) and Google Pixel devices (70%), then processed with deepfake technology. The dataset covers multiple resolutions, including 1080p, 720p, and 480p, supporting a wide range of video detection methods.
How was the data collected?
The dataset was built by generating fake faces using AI models and overlaying them on real videos (using the following tools: aisaver.io, faceswapvideo.ai, and magichour.ai).
What metadata is included with the dataset?
Each video includes technical metadata such as age, gender, and ethnicity, supporting demographic analysis and balanced model training. The dataset also preserves video characteristics including resolution, duration, frame rate, and recording device for benchmarking deep learning models.
Is it possible to request a custom deepfake dataset?
Custom datasets can be created on request, allowing you to specify generation methods, annotation formats, or target demographics. This flexibility ensures better results for applications such as face recognition, synthetic video detection, or generative AI model training.
How can this dataset improve deepfake detection models?
The dataset provides paired real-world video characteristics with AI-generated facial manipulations, making it valuable for training deepfake detection and facial recognition models. Its diverse demographics, multiple video resolutions, and realistic head movements help improve model robustness across different attack scenarios.
How are Unidata datasets licensed?
Unidata datasets follow a dual-licensing model. Free samples are available for testing and evaluation, while full datasets, including the Deepfake Videos Dataset, can be accessed exclusively through purchase.
How are Unidata datasets stored?
Unidata securely stores datasets on AWS cloud infrastructure, ensuring high availability and scalability. Our storage practices comply with ISO 27001 and ISO 27701 standards, guaranteeing internationally recognized information security and privacy management for sensitive data.
How long does it take to receive the dataset?
Once you submit a request, our team will contact you to confirm details and finalize documentation. After signing and payment, the dataset will be delivered within 3–10 business days.
Is this a real-world dataset or synthetic data?
The Deepfake Videos Dataset is a synthetic video dataset created by combining real-world source videos with AI-generated faces. This hybrid approach provides realistic training material for developing deepfake detection methods, recognition models, and generative AI research.
Still have questions about using Unidata datasets?
Read our user-guides
Unidata Cases
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