EucliDreamer: Fast and High-Quality Texturing for 3D Models with
  Depth-Conditioned Stable Diffusion
Cindy Le Congrui Hetang Chendi Lin Ang Cao Yihui He
We present EucliDreamer, a simple and effective method to generate textures
for 3D models given text prompts and meshes. The texture is parametrized as an
implicit function on the 3D surface, which is optimized with the Score
Distillation Sampling (SDS) process and differentiable rendering. To generate
high-quality textures, we leverage a depth-conditioned Stable Diffusion model
guided by the depth image rendered from the mesh. We test our approach on 3D
models in Objaverse and conducted a user study, which shows its superior
quality compared to existing texturing methods like Text2Tex. In addition, our
method converges 2 times faster than DreamFusion. Through text prompting,
textures of diverse art styles can be produced. We hope Euclidreamer proides a
viable solution to automate a labor-intensive stage in 3D content creation.