用2D高斯点云直接生成文本到3D的表面，效果逼真多样。
Generating Surface for Text-to-3D using 2D Gaussian Splatting
- 基于条件文本生成与多视角纹理法线先验，用2D高斯点云渲染3D表面。
- 引入曲率约束优化，解决多视角几何不一致问题，提升表面质量。
- 适合需要快速生成高质量3D模型的研究者和创作者使用。
文本到3D建模近年来展现出巨大潜力，但自然物体复杂的几何结构仍使3D内容生成极具挑战。现有方法或利用2D扩散先验恢复3D几何，或直接基于特定3D表示训练模型。本文提出一种新方法DirectGaussian，专注于以表面元素（surfels）表示的3D对象表面生成。该方法结合条件文本生成模型，通过多视角法线与纹理先验，使用2D高斯点云进行表面渲染。为解决多视角几何一致性问题，DirectGaussian在优化过程中引入曲率约束。大量实验表明，本框架能实现多样化且高保真的3D内容生成。
原文摘要 · Abstract (English)
Recent advancements in Text-to-3D modeling have shown significant potential for the creation of 3D content. However, due to the complex geometric shapes of objects in the natural world, generating 3D content remains a challenging task. Current methods either leverage 2D diffusion priors to recover 3D geometry, or train the model directly based on specific 3D representations. In this paper, we propose a novel method named DirectGaussian, which focuses on generating the surfaces of 3D objects represented by surfels. In DirectGaussian, we utilize conditional text generation models and the surface of a 3D object is rendered by 2D Gaussian splatting with multi-view normal and texture priors. For multi-view geometric consistency problems, DirectGaussian incorporates curvature constraints on the generated surface during optimization process. Through extensive experiments, we demonstrate that our framework is capable of achieving diverse and high-fidelity 3D content creation.
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