One-to-many Reconstruction of 3D Geometry of cultural Artifacts using a
  synthetically trained Generative Model
Thomas Pöllabauer Julius Kühn Jiayi Li Arjan Kuijper
Estimating the 3D shape of an object using a single image is a difficult
problem. Modern approaches achieve good results for general objects, based on
real photographs, but worse results on less expressive representations such as
historic sketches. Our automated approach generates a variety of detailed 3D
representation from a single sketch, depicting a medieval statue, and can be
guided by multi-modal inputs, such as text prompts. It relies solely on
synthetic data for training, making it adoptable even in cases of only small
numbers of training examples. Our solution allows domain experts such as a
curators to interactively reconstruct potential appearances of lost artifacts.