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WuJi has open-sourced its MINT model and EgoPipeline for reconstructing 3D hand and camera motion from first-person video, along with 1,021 hours of egocentric data to aid robot learning.
The article discusses the potential benefits and challenges of using first-person video for robot learning, highlighting that while direct imitation is limited, the sequence of visual attention may transfer. It references LingBot-VLA 2.0 and calls for controlled evaluations to separate viewpoint effects from data volume.
EgoCS-400K is a large-scale egocentric Counter-Strike dataset with over 400,000 first-person videos and 10,000 hours of gameplay, providing temporally aligned video-action-language trajectories for world model research.
A 25-year-old housewife in Chennai earns ₹250/hour filming her daily housework for AI companies training humanoid robots, as part of a growing gig economy where thousands in India record everyday tasks to train future robots.