Today, the Bytedance Seed team launched a large 3D generated model - Seed3D 1.0, which enables end-to-end generation from a single image to a high-quality simulation-level 3D model.Seed3D 1.0 is based on the innovative Diffusion Transformer architecture and is completed through large-scale data training to generate complete 3D models including fine geometry, real textures and physically based rendering (PBR) materials.
3D models generated through Seed3D 1.0 can be seamlessly imported into simulation engines such as Isaac Sim, and only a small amount of adaptation work is required to support embodied intelligent large model training.
In addition, through step-by-step scene generation, Seed3D 1.0 can expand from single object generation to constructing complete 3D scenes.
In comparison with existing 3D generation models, Seed3D 1.0 shows advantages: its texture and material generation performance exceeds previous open source and closed source models, its geometry generation performance exceeds that of models with larger parameter scales in the industry, and its comprehensive capabilities reach the industry-leading level.
At present, the Seed3D 1.0 technical report has been made public, and the API has also been launched. You can visit the project homepage to view: project homepage, experience portal
Seed3D 1.0 uses Diffusion Transformer, a model architecture widely used in generative AI, to design 3D geometry generation and texture mapping models.
Using a step-by-step generation strategy, Seed3D 1.0 can also be expanded from generating a single object to generating a complete and coherent 3D scene.
According to actual measurements, Seed3D 1.0 has fewer geometry generation parameters and better effects; the images generated by texture materials maintain leading performance.
