What is Kiss3DGen
Kiss3DGen is an innovative 3D asset generation framework that efficiently generates, edits, and enhances 3D objects by repurposing pretrained 2D image diffusion models. Its core lies in generating a "3D Bundle Image," which combines multi-view images and their corresponding normal maps into a collage representation. The normal maps are used to reconstruct the 3D mesh, while the multi-view images provide texture mapping. It transforms the complex 3D generation problem into a 2D image generation task, fully leveraging the knowledge of pretrained diffusion models, is compatible with various diffusion model techniques, and supports functions such as 3D editing, mesh and texture enhancement.
Main features of Kiss3DGen
- Text-to-3D generation: Users can generate high-quality 3D models through simple text descriptions.
- Image-to-3D generation: The framework can convert 2D images into 3D models, making it suitable for extending existing image content into three-dimensional space.
- Hybrid generation workflow: Users can combine image-to-3D and text-guided mesh editing to create complex 3D scenes.
- Combination of multi-view images and normal maps: The framework generates a "3D Bundle Image," that is, a collage representation of multi-view images and their corresponding normal maps. The normal maps are used to reconstruct the 3D mesh, and the multi-view images provide texture mapping, generating a complete 3D model.
- Support for multiple editing functions: Kiss3DGen supports generating 3D models, is compatible with various diffusion model techniques, and supports functions such as 3D editing, mesh and texture enhancement.
- Efficient training and inference: The framework performs well with limited training data and can quickly generate high-quality 3D models.
- Multi-task generation capability: Kiss3DGen can simultaneously handle multiple generation tasks, including generating 3D models from text or images, editing existing 3D models, and improving the quality of 3D assets.
Technical principles of Kiss3DGen
- Repurposing 2D diffusion models: The core idea of Kiss3DGen is to transform the 3D generation problem into a 2D image generation problem. By fine-tuning pretrained 2D diffusion models (such as Stable Diffusion), the framework can build on existing powerful 2D generation capabilities and avoid training complex 3D generation models from scratch.
- 3D Bundle Image: The framework introduces the concept of "3D Bundle Image," which is a collage representation composed of multi-view images and their corresponding normal maps. It can extract enough information from 2D images to reconstruct a complete 3D model.
- Normal map enhancement: Normal maps are one of the key technologies of Kiss3DGen. By capturing directional information of object surfaces, they help the model reconstruct more accurate 3D geometric shapes. The introduction of normal maps makes the conversion from 2D to 3D more efficient and accurate.
- ControlNet technology: To achieve more precise 3D editing, Kiss3DGen introduces ControlNet technology. Users can make local modifications to generated 3D models through text prompts or spatial cues, enabling more flexible editing functions.
Project address of Kiss3DGen
- Project official website：https://ltt-o.github.io/Kiss3dgen.github.io/
- Github repository：https://github.com/EnVision-Research/Kiss3DGen
- arXiv technical paper：https://arxiv.org/pdf/2503.01370
- Online experience Demo：https://huggingface.co/spaces/LTT/Kiss3DGen
Application scenarios of Kiss3DGen
- Game development: Developers can directly generate 3D assets required for games, such as characters, props, and scenes, through text descriptions or image input.
- Film and television production: In film and television special effects and animation production, Kiss3DGen can be used to quickly generate complex 3D scenes and character models.
- Virtual Reality (VR) and Augmented Reality (AR): 3D models generated by Kiss3DGen can be directly used in VR and AR applications. In VR scenarios, users can generate personalized virtual environments or objects through simple text descriptions, enhancing immersion.
- Digital Twins: Kiss3DGen can be used to generate digital twin models, such as urban buildings, industrial equipment, etc. Kiss3DGen can quickly build high-precision digital twin scenes, providing support for applications such as smart cities and Industry 4.0.
- Education and Training: In the field of education, Kiss3DGen can generate 3D models for teaching, such as historical artifacts, biological models, etc., helping students understand complex concepts more intuitively.