Kiss3DGen Simplifies 3D Model Generation Using 2D Image Diffusion Models

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From 2D to 3D: Kiss3DGen Uses Image Diffusion Models for 3D Object Generation
Generating 3D content remains a challenge despite advancements in artificial intelligence. While 2D image generators achieve impressive results, the quality and generalizability of 3D models often lag behind. A major problem is the acquisition of training data: Large datasets with 3D assets are time-consuming and expensive to create. Kiss3DGen ("Keep It Simple and Straightforward in 3D Generation") pursues a new approach to overcome this hurdle. The method uses pre-trained 2D image diffusion models and adapts them for 3D generation, thereby reducing the need for extensive 3D training data.
At the heart of Kiss3DGen is the generation of so-called "3D Bundle Images". This is a tiled representation that combines multiple views of an object along with the corresponding normal maps. Normal maps contain information about the surface normal at each point of the object and are essential for reconstructing the 3D geometry. The different views of the object are then used to texture the generated 3D model.
This approach effectively reduces the complex task of 3D generation to a 2D image generation task. The knowledge embedded in the pre-trained diffusion models can thus be optimally utilized. Another advantage of Kiss3DGen is its compatibility with various techniques for diffusion models. This enables advanced features such as editing 3D models, improving mesh quality and textures, and further application possibilities.
Efficiency and Quality in Focus
Kiss3DGen is characterized by its efficiency. By using pre-trained models, the computational effort for training is significantly reduced. Experiments show that the method can generate high-quality 3D models. The results demonstrate the potential of this approach to simplify and accelerate 3D generation.
Future Perspectives and Application Possibilities
Developments in the field of 3D generation are dynamic. Kiss3DGen represents a promising step towards closing the gap between 2D and 3D content. The application possibilities are diverse and range from the creation of 3D assets for games and virtual worlds to the generation of models for product design and architecture. Further research in this area will show the potential of this approach and how it will influence the future of 3D modeling.
Mindverse: AI Solutions for Content Creation
The development of AI-powered tools like Kiss3DGen is changing the way we create content. Mindverse, a German company specializing in AI solutions, offers an all-in-one platform for generating text, images, and 3D models. In addition to standardized tools, Mindverse also develops customized solutions such as chatbots, voicebots, AI search engines, and knowledge systems for companies. The integration of innovative technologies like Kiss3DGen into such platforms allows users to make complex tasks like 3D modeling more efficient and accessible.
Bibliographie: - https://huggingface.co/papers/2503.01370 - https://huggingface.co/papers - https://openreview.net/forum?id=eajZpoQkGK - https://github.com/chenguolin/DiffSplat - https://arxiv.org/abs/2306.08103 - https://www.researchgate.net/publication/388459849_DiffSplat_Repurposing_Image_Diffusion_Models_for_Scalable_Gaussian_Splat_Generation - https://arxiv.org/html/2408.03178v1 - https://silent-chen.github.io/PartGen/ - https://openreview.net/pdf/725a3a29056638e240a903a60938735d3fccd156.pdf ```