  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.
