An Implicit Parametric Morphable Dental Model
This work addresses a gap in dental modeling for medical and reconstruction applications by including both teeth and gum, though it is incremental as it builds on existing morphable model techniques.
The paper tackles the lack of a parametric 3D morphable dental model that includes both teeth and gum, presenting the first such model using an implicit scene representation, which achieves reconstruction quality comparable to advanced global implicit representations and enables applications like segmentation and tooth replacement.
3D Morphable models of the human body capture variations among subjects and are useful in reconstruction and editing applications. Current dental models use an explicit mesh scene representation and model only the teeth, ignoring the gum. In this work, we present the first parametric 3D morphable dental model for both teeth and gum. Our model uses an implicit scene representation and is learned from rigidly aligned scans. It is based on a component-wise representation for each tooth and the gum, together with a learnable latent code for each of such components. It also learns a template shape thus enabling several applications such as segmentation, interpolation, and tooth replacement. Our reconstruction quality is on par with the most advanced global implicit representations while enabling novel applications. Project page: https://vcai.mpi-inf.mpg.de/projects/DMM/