Abstract
We introduce LivingWorld, an interactive framework for generating 4D worlds with environmental dynamics from a single image. While recent advances in 3D scene generation enable large-scale environment creation, most approaches focus primarily on reconstructing static geometry, leaving scene-scale environmental dynamics such as clouds, water, or smoke largely unexplored. Modeling such dynamics is challenging because motion must remain coherent across an expanding scene while supporting low-latency user feedback. LivingWorld addresses this challenge by progressively constructing a globally coherent motion field as the scene expands. To maintain global consistency during expansion, we introduce a geometry-aware alignment module that resolves directional and scale ambiguities across views. We further represent motion using a compact hash-based motion field, enabling efficient querying and stable propagation of dynamics throughout the scene. This representation also supports bidirectional motion propagation during rendering, producing long and temporally coherent 4D sequences without relying on expensive video-based refinement. On a single RTX 5090 GPU, generating each new scene expansion step requires 9 seconds, followed by 3 seconds for motion alignment and motion field updates, enabling interactive 4D world generation with globally coherent environmental dynamics. Video demonstrations are available at this http URL.
Abstract (translated)
我们介绍了LivingWorld，这是一个从单张图像生成具有环境动态的4D世界的交互式框架。尽管近期3D场景生成的进展实现了大规模环境创建，但大多数方法主要侧重于重建静态几何，而场景尺度的环境动态（如云、水或烟雾）仍 largely unexplored。建模此类动态具有挑战性，因为运动必须在场景扩展过程中保持连贯，同时支持低延迟的用户反馈。LivingWorld通过随着场景扩展渐进构建全局连贯的运动场来解决这一挑战。为在扩展过程中维持全局一致性，我们引入了几何感知对齐模块，以解决跨视图的方向和尺度模糊性。我们进一步采用基于哈希的紧凑运动场来表示运动，实现高效查询以及动态在场景中的稳定传播。该表示还支持渲染过程中的双向运动传播，无需依赖昂贵的基于视频的细化即可生成长时间且时序连贯的4D序列。在单块RTX 5090 GPU上，每个新场景扩展步骤的生成需要9秒，随后进行3秒的运动对齐与运动场更新，从而实现具有全局连贯环境动态的交互式4D世界生成。视频演示可在此http URL查看。
URL
https://arxiv.org/abs/2604.01641
