# EgoXperience: Learning World-Aligned Egocentric Representations from Human Experience

- Source: HuggingFace Daily Papers
- Published: 2026-10-19T00:00:00.000Z
- RoboHot: https://robohot.news/en/items/q90jpop7ut5vj7kefqpnt49s6
- Original: https://huggingface.co/papers/2610.26625

## Summary

EgoXperience proposes a complete pipeline covering data collection, automatic annotation, unified modeling, and benchmark evaluation, aimed at jointly reconstructing observer motion, scene geometry, and hand-object interactions from egocentric video. At its core is the automatic annotation engine EgoXX-Engine, which combines geometrically verified object tracking with SLAM-based world alignment to produce the 50-hour dataset EgoX-Data-6M (with second-level task descriptions) and the 1-hour evaluation set EgoX-Bench.