Fantasia3D is a text-to-3D content generation method, published by South China University of Technology at ICCV 2023. The core of this method is to decouple the modeling and learning of geometry and appearance to generate high-quality 3D assets.
Uses
- Text-to-3D content generation: Generate high-quality 3D assets based on pure text prompts (zero-shot generation).
- User-guided generation: Can accept user-customized 3D models as initialization for guided asset generation.
Main capabilities
- Geometry learning: Uses a hybrid scene representation (DMTET, initialized as a 3D ellipsoid), and optimizes by taking the surface normals of the extracted mesh (in the early stage of training, also including object masks) as input to an image diffusion model (Stable Diffusion).
- Appearance modeling: Introduces a spatially varying bidirectional reflectance distribution function (BRDF) in the text-to-3D task, learning to predict three components of appearance (kd, krm, kn) to achieve photorealistic rendering of the generated surface.
- The decoupled framework is more compatible with graphics engines, supporting relighting, editing, and physical simulation of generated 3D assets.
- Both geometry and appearance modeling are supervised through the Score Distillation Sampling (SDS) loss.
Usage No specific installation commands, code repository addresses, or operation steps are provided in the materials. The page address is https://fantasia3d.github.io/ . You can visit this page to obtain project-related information.
Applicable scenarios
- Text-driven 3D asset creation.
- Scenarios requiring decoupled geometry and appearance for subsequent relighting, editing, or physical simulation.
- Guided generation scenarios using custom 3D models as initialization.
Limitations
- The materials do not provide information on fees, pricing, platform support, performance metrics, or usage thresholds.
- No specific quantitative result data is provided in the experiments; it only states that its method outperforms existing methods under different text-to-3D task settings.
