3D generation guided by text-to-image diffusion models enables the creation
of visually compelling assets. However previous methods explore generation
based on image or text. The boundaries of creativity are limited by what can be
expressed through words or the images that can be sourced. We present YouDream,
a method to generate high-quality anatomically controllable animals. YouDream
is guided using a text-to-image diffusion model controlled by 2D views of a 3D
pose prior. Our method generates 3D animals that are not possible to create
using previous text-to-3D generative methods. Additionally, our method is
capable of preserving anatomic consistency in the generated animals, an area
where prior text-to-3D approaches often struggle. Moreover, we design a fully
automated pipeline for generating commonly found animals. To circumvent the
need for human intervention to create a 3D pose, we propose a multi-agent LLM
that adapts poses from a limited library of animal 3D poses to represent the
desired animal. A user study conducted on the outcomes of YouDream demonstrates
the preference of the animal models generated by our method over others.
Turntable results and code are released at this https URL

使用文本到图像扩散模型指导的 3D 生成方法能够创建具有视觉吸引力的资产，我们提出了一种名为 YouDream 的方法，通过二维视图控制 3D 姿势先验来生成高质量的具备解剖学控制的动物，该方法能够生成以往的文本到 3D 生成方法不能实现的 3D 动物，并且在保持解剖一致性方面表现出色。