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100K Hours Egocentric Dataset for Embodied AI & Robot Manipulation
egocentric dataset
robot manipulation dataset
embodied AI dataset
VLA dataset
multimodal robotics dataset
first person video dataset
human pose dataset
3D reconstruction dataset
This large-scale egocentric dataset includes over 100,000 hours of human manipulation data captured from a first-person perspective across diverse real-world scenarios. Each data sample includes synchronized multimodal information: binocular video, camera parameters, 3D scene reconstruction point clouds, human joint tracking, and stepwise semantic annotations. It is designed to train embodied AI and Vision-Language-Action (VLA) models, enabling systems to learn from human demonstrations in realistic environments.
This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.
![Specifications]()
Specifications
Data content
100,000 hours of human manipulation data captured from a first-person view across real-world scenarios. Each record includes: ①time-aligned binocular video, ②binocular camera parameters, ③3D scene reconstruction point cloud file, ④human body joint data, ⑤stepwise semantic annotation file
Collection devices
PICO 4 Ultra headset worn on the head, and IMU wristbands worn on both wrists
Data distribution
real-world scenarios(like kitchen, room, hotel, etc.) that including multiple daily manipulation tasks(like food preparation & cooking, cleaning, object organizing & storage, bed making, clothing folding, etc.)
![Sample]()
Sample
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