Paper recorded by Signals 4 on 2026-10-15 in cs.AI. Abstract reproduced from arXiv; link to the original below.
Published 2026-10-15 on arXiv · recorded by Signals 4 on 2026-10-16
Category: cs.AI · 人工智能 · first seen 2026-10-16
Recent 3D world models increasingly use features from geometry foundation models (GFMs) as predictive world states, benefiting from their rich geometric priors. However, the view dependence of these features entangles scene dynamics with camera-induced variation, making the resulting state evolution harder to predict. We propose GeoState, a view-decoupled geometry representation for predictive 3D