We target a 3D generative model for general natural scenes that are typically unique and intricate. Lacking the necessary volumes of training data, along with the difficulties of having ad hoc designs in presence of varying scene characteristics, renders existing setups intractable. Inspired by classical patch-based image models, we advocate for synthesizing 3D scenes at the patch level, given a single example. At the core of this work lies important algorithmic designs w.r.t the scene representation and generative patch nearest-neighbor module, that address unique challenges arising from lifting classical 2D patch-based framework to 3D generation. These design choices, on a collective level, contribute to a robust, effective, and efficient model that can generate high-quality general natural scenes with both realistic geometric structure and visual appearance, in large quantities and varieties, as demonstrated upon a variety of exemplar scenes.

翻译：针对通常具有独特性和复杂性的通用自然场景，我们提出了一种3D生成模型。缺乏必要的训练数据量，以及面对不同场景特征时需进行特殊设计的困难，使得现有方法难以实施。受经典基于块的图像模型启发，我们主张在给定单个示例的情况下，从块级别合成3D场景。本工作的核心贡献在于针对场景表示和生成性块最近邻模块的重要算法设计，这些设计解决了将经典2D块框架提升至3D生成时面临的独特挑战。这些集体层面的设计选择，共同构建了一个鲁棒、高效且有效的模型。该模型能够批量生成大量多样化的高质量通用自然场景，在多个示例场景上的实验表明其兼具真实的几何结构与视觉外观。