无需训练即可生成大尺度高精度3D世界，结合2D与3D生成优势。
SynCity: Training-Free Generation of 3D Worlds
- 用瓦片式拼接方法，逐块生成并融合3D场景。
- 可扩展生成大型复杂场景，保持布局与外观一致性。
- 适合游戏、影视等需要快速构建3D环境的领域。
我们解决从文本描述生成3D世界的问题。提出SynCity，一种无需训练和优化的方法，利用预训练3D生成模型的几何精度和2D图像生成器的艺术多样性，创建大规模、高质量的3D空间。现有3D生成模型多以物体为中心，难以生成大尺度场景，我们通过结合3D与2D生成器实现场景无限扩展。采用瓦片式方法，可精细控制场景布局与外观。世界按瓦片逐块生成，每块在上下文环境中生成后融合到整体场景中。SynCity生成的场景细节丰富、风格多样，具有高度沉浸感。
原文摘要 · Abstract (English)
We address the challenge of generating 3D worlds from textual descriptions. We propose SynCity, a training- and optimization-free approach, which leverages the geometric precision of pre-trained 3D generative models and the artistic versatility of 2D image generators to create large, high-quality 3D spaces. While most 3D generative models are object-centric and cannot generate large-scale worlds, we show how 3D and 2D generators can be combined to generate ever-expanding scenes. Through a tile-based approach, we allow fine-grained control over the layout and the appearance of scenes. The world is generated tile-by-tile, and each new tile is generated within its world-context and then fused with the scene. SynCity generates compelling and immersive scenes that are rich in detail and diversity.
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