We propose a novel technique for adding geometric details to an input coarse 3D mesh guided by a text prompt. Our method is composed of three stages. First, we generate a single-view RGB image conditioned on the input coarse geometry and the input text prompt. This single-view image generation step allows the user to pre-visualize the result and offers stronger conditioning for subsequent multi-view generation. Second, we use our novel multi-view normal generation architecture to jointly generate six different views of the normal images. The joint view generation reduces inconsistencies and leads to sharper details. Third, we optimize our mesh with respect to all views and generate a fine, detailed geometry as output. The resulting method produces an output within seconds and offers explicit user control over the coarse structure, pose, and desired details of the resulting 3D mesh. Project page: https://text-mesh-refinement.github.io.

我们提出了一种新颖的技术，通过文本提示为输入的粗糙3D网格添加几何细节。我们的方法由三个阶段组成：首先，我们基于输入的粗糙几何和输入的文本提示生成一个与之相关的单视角RGB图像；其次，我们使用新颖的多视角法线生成架构共同生成六个不同视角的法线图像；最后，我们对网格进行优化，生成细致的几何输出。该方法在几秒钟内产生输出，并提供对生成的3D网格的粗略结构、姿势和所需细节的明确用户控制。

基于文本引导的可控网格精细化方法用于交互式三维建模