Pai Chai University

The study proposes a software-only method that reconstructs a 3D oral model from only ten 2D intraoral images captured from different angles, requiring no dedicated hardware; the model is trained on the public Teeth3DS dataset of 950 upper jaw samples and uses MobileNetV2 as the image encoder with Multi-head Attention for multi-view feature fusion, achieving 77.49% accuracy under nearest-neighbor matching with a distance threshold of 0.035, while predicted vertices tend to concentrate in high-density regions of the ground truth, producing uneven point distribution in the reconstructed model.

The study proposes a software-only method that reconstructs a 3D oral model from only ten 2D intraoral images captured from different angles, requiring no dedicated hardware; the model is trained on the public Teeth3DS dataset of 950 upper jaw samples and uses MobileNetV2 as the image encoder with Multi-head Attention for multi-view feature fusion, achieving 77.49% accuracy under nearest-neighbor matching with a distance threshold of 0.035, while predicted vertices tend to concentrate in high-density regions of the ground truth, producing uneven point distribution in the reconstructed model.