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What 30,000 Hours of Ego-centric Video Does Not Teach

Paper recorded by Signals 4 on 2026-10-08 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-08 on arXiv · recorded by Signals 4 on 2026-10-09

Category: cs.CV · 计算机视觉 · first seen 2026-10-09

Abstract

World models offer a promising alternative to physics-based simulators, yet remain far from practical deployment. We ask how far scaling ego-centric human video takes them, using a dataset of 30,000 hours spanning over 1,000 scene types and 14,000 contributors. Rather than relying on opaque downstream metrics, we directly evaluate agent and object-interaction fidelity on a challenging out-of-distr

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#307 most recent of 756 cs.CV papers we have recorded · ↑ newer: DreamTrue: Action-Faithful Robot World Model with Counterfactual Post- · ↓ older: OuroWorld: Bringing Any 3D World Alive as Diverse, Endlessly Looping 3
Cite this page: What 30,000 Hours of Ego-centric Video Does Not Teach: the #307 most recent of 756 cs.CV papers we have recorded (as of 2026-10-08). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/what-30-000-hours-of-ego-centric-video-does-not-teach.html
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