The photorealistic reconstruction and rendering of architectural scenes have extensive applications in industries such as film, games, and transportation. It also plays an important role in urban planning, architectural design, and the city's promotion, especially in protecting historical and cultural relics. The 3D Gaussian Splatting, due to better performance over NeRF, has become a mainstream technology in 3D reconstruction. Its only input is a set of images but it relies heavily on geometric parameters computed by the SfM process. At the same time, there is an existing abundance of raw 3D models, that could inform the structural perception of certain buildings but cannot be applied. In this paper, we propose a straightforward method to harness these raw 3D models to guide 3D Gaussians in capturing the basic shape of the building and improve the visual quality of textures and details when photos are captured non-systematically. This exploration opens up new possibilities for improving the effectiveness of 3D reconstruction techniques in the field of architectural design.
建筑场景的真实感重建和渲染在电影、游戏和交通等行业有广泛应用。它在城市规划、建筑设计和城市宣传中也发挥着重要作用,尤其是在保护历史文化遗迹方面。由于比NeRF表现更好,3D高斯喷溅已成为3D重建的主流技术。它的唯一输入是一组图像,但它严重依赖于SfM过程计算的几何参数。同时,现有大量原始3D模型可以提供某些建筑的结构感知,但无法直接应用。在本文中,我们提出了一种直接的方法来利用这些原始3D模型来指导3D高斯分布捕捉建筑物的基本形状,并在非系统性拍摄照片时改善纹理和细节的视觉质量。这一探索为提高建筑设计领域3D重建技术的有效性开辟了新的可能性。