Abstract
Perpetual 3D scene generation aims to produce long-range and coherent 3D view sequences, which is applicable for long-term video synthesis and 3D scene reconstruction. Existing methods follow a "navigate-and-imagine" fashion and rely on outpainting for successive view expansion. However, the generated view sequences suffer from semantic drift issue derived from the accumulated deviation of the outpainting module. To tackle this challenge, we propose ScenePainter, a new framework for semantically consistent 3D scene generation, which aligns the outpainter's scene-specific prior with the comprehension of the current scene. To be specific, we introduce a hierarchical graph structure dubbed SceneConceptGraph to construct relations among multi-level scene concepts, which directs the outpainter for consistent novel views and can be dynamically refined to enhance diversity. Extensive experiments demonstrate that our framework overcomes the semantic drift issue and generates more consistent and immersive 3D view sequences. Project Page: this https URL.
Abstract (translated)
持续的3D场景生成旨在生成长跨度且连贯的3D视图序列，这适用于长期视频合成和3D场景重建。现有方法遵循“导航与想象”的方式，并依赖于扩展（outpainting）来实现连续视图的扩展。然而，所生成的视图序列会因累积误差导致语义漂移问题。为解决这一挑战，我们提出了ScenePainter，这是一个新的框架，用于生成语义上一致的3D场景，它通过将扩展器的特定于场景的先验知识与当前场景的理解进行对齐来实现这一目标。 具体而言，我们引入了一种层次化的图结构，名为SceneConceptGraph，用以构建多级场景概念之间的关系。这种图结构可以指导生成器产生一致的新视图，并且可以通过动态细化增强多样性。 广泛的实验表明，我们的框架能够克服语义漂移问题，并生成更为一致和沉浸式的3D视图序列。 项目页面：[此链接](this https URL)。
URL
https://arxiv.org/abs/2507.19058
