DeepFake Videos Dataset - 5,000 Files for Facial Recognition and Computer Vision

Overview DeepFake Videos Dataset is a commercial synthetic video dataset produced by the provider, containing 5,000 video files featuring real people with AI-generated faces overlaid. Designed specifically for deepfake detection, facial recognition, and computer vision research, it provides realistic and diverse training material for building and benchmarking deepfake detectors and detection algorithms. Each video was created by generating fake faces and overlaying them onto authentic source videos of real individuals turning their heads in different directions. Dataset Composition - 5,000 video files, each corresponding to a unique person - 5,000 unique subjects with individual metadata records - AI face generation sources: aisaver.io, faceswapvideo.ai, magichour.ai - Data type: real videos with AI-generated faces overlaid - Labeling: metadata per subject — age, gender, ethnicity Subject Demographics Both male and female participants are represented in the dataset: - Gender breakdown: Male and Female subjects - Ethnicity breakdown: Asian (30%), African (70%) - Age range: Min = 18, Max = 80, Mean = 45 Each video is labeled with structured metadata covering age, gender, and ethnicity, enabling targeted filtering and stratified model training across demographic groups. Technical Specifications - Formats: MP4, MOV - Resolutions: 1920×1080p, 1280×720p, 720×480p, 640×480p, 480×360p, 1920×920p - Video duration: Mean = 9 sec, Median = 9 sec, Min = 2 sec, Max = 34 sec - Frames per second: