AI technology for detailing capabilities
3D Bust Maker's core AI algorithm includes a specialized neural network architecture to process facial features. The system first identifies 68 key points of the face to localize through a convolutional neural network, and then employs a generative adversarial network (GAN) to construct a 3D topology. In the detail processing stage, the algorithm focuses on enhancing features at three levels: 1) macro-structural contour accuracy, 2) meso-level proportions of the features, and 3) micro-details such as skin texture and hair direction.
Platform tests show that for input photos with a resolution of 300 dpi or higher, the generated model can reproduce facial details at the 0.1mm level, which is the exact standard of accuracy required for professional-grade 3D printing. The system also has a built-in post-processing optimization module that automatically fixes common modeling defects such as non-flowing edges or hole problems, ensuring that the output model meets the topological requirements for 3D printing.
This answer comes from the article3D Bust Maker: Generating 3D Printed Busts from a Single Photo》
