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L3G-World: Real-Time Infinite World Generation with Latent 3D Gaussian Memory

Paper recorded by Signals 4 on 2026-10-29 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-29 on arXiv · recorded by Signals 4 on 2026-10-30

Category: cs.CV · 计算机视觉 · first seen 2026-10-30

Abstract

Interactive world models generate visual content conditioned on user actions, yet maintaining spatial consistency over long-horizon exploration in real time remains challenging. Existing approaches rely on either temporal context or explicit 3D memory, both of which scale poorly because memory grows with the length of the generated stream. Moreover, explicit 3D memories condition latent video gene

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#53 most recent of 710 cs.CV papers we have recorded · ↑ newer: SymAnt: Grounding Long-Horizon Action Anticipation with Adaptable Symb · ↓ older: Fight World Model: Customizable Combat through Visual Interaction Prox
Cite this page: L3G-World: Real-Time Infinite World Generation with Latent 3D Gaussian Memory: the #53 most recent of 710 cs.CV papers we have recorded (as of 2026-10-29). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/l3g-world-real-time-infinite-world-generation-with-latent-3d-gaussian-memory.html
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