  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.
