2K+ Hours of Face id Video Data | AI Training Data | Annotated Video for AI | Bounding Boxes, Action Labels & Scene Descriptions | Global
Overview
2K+ Hours of Face id Video Data | AI Training Data | Annotated Video for AI | Bounding Boxes, Action Labels & Scene Descriptions | Global is a video and image dataset. The provider states a volume of 2,000 hours. Typical applications include object detection and segmentation. Relevant sectors: AI & Machine Learning and Education. The listing mentions transcription, bounding boxes and polygons / segmentation. Pricing is not published and is provided on request.
Primary applications
What the listing offers
- Stated volume of 2,000 hours.
- Listing mentions transcription, bounding boxes, polygons / segmentation.
This dataset contains over 2,000 hours of face ID selfie video recordings captured worldwide. Designed for AI and machine-learning applications, it provides richly annotated, context-dense video data suitable for training vision-language models, action-recognition systems, identity-aware AI, and multimodal reasoning. Key Features 1. Comprehensive Video Annotation Layers Each video includes synchronized metadata across visual and audio channels, such as: Object annotations (bounding boxes, segmentation masks) Action labels and activity timelines Temporal event boundaries Transcripts for scenes containing speech Visual scene descriptions covering environment, objects, actions, and context Camera metadata (motion type, angle, field of view, lighting conditions) This supports training for identity-aware video analysis, activity detection, video captioning, tracking, VLM grounding, and multimodal understanding. 2. Unique Sourcing Capabilities Videos are collected through controlled contribution pipelines designed to generate authentic, unscripted real-world footage. This provides: Natural human movement and behavior Diverse environments and camera devices Continuous flow of fresh recordings Ability to generate custom datasets (e.g., specific actions, environments, lighting conditions, demographics, or motion patterns) 3. Global Visual & Cultural Diversity Contributors from 100+ countries supply: Indoor and outdoor recordings Urban, rural, and specialized environments Varied cultur
Related datasets
More in Video & Physical AI →100K+ Hours of Video Data | AI Training Data | Annotated Video for AI | Bounding Boxes, Action Labels & Scene Descriptions | Global Coverage
This dataset contains over 100,000 hours of video recordings captured worldwide.
- Language
- —
- Volume
- 100k h
- Domain
- AI & Machine Learning +1
- Use case
- Object detection
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