Shap-E

For graphic designers, digital artists and game developers, 3D content creation can be among the most complex and time-consuming tasks, often taking hours - sometimes days - to create a moderately complex 3D object. Stability AI is pleased to introduce a private preview of Stable 3D, an automatic process to generate concept-quality textured 3D objects that eliminates much of that complexity and allows a non-expert to generate a draft-quality 3D model in minutes, by selecting an image or illustration, or writing a text prompt. Objects created with Stable 3D are delivered in the “.obj” standard file format, and can be further edited and improved in 3D tools like Blender and Maya, or imported in a game engine, such as Unreal Engine 5 or Unity.

Text2Mesh produces color and geometric details over a variety of source meshes, driven by a target text prompt. Our stylization results coherently blend unique and ostensibly unrelated combinations of text, capturing both global semantics and part-aware attributes. Our framework, Text2Mesh, stylizes a 3D mesh by predicting color and local geometric details which conform to a target text prompt. We consider a disentangled representation of a 3D object using a fixed mesh input (content) coupled with a learned neural network, which we term neural style field network. In order to modify style, we obtain a similarity score between a text prompt (describing style) and a stylized mesh by harnessing the representational power of CLIP. Text2Mesh requires neither a pre-trained generative model nor a specialized 3D mesh dataset. It can handle low-quality meshes (non-manifold, boundaries, etc.) with arbitrary genus, and does not require UV parameterization.