Pix2Repair: Implicit Shape Restoration from Images

We present Pix2Repair, an automated shape repair approach that generates restoration shapes from images to repair fractured objects. Prior repair approaches require a high-resolution watertight 3D mesh of the fractured object as input. Input 3D meshes must be obtained using expensive 3D scanners, and scanned meshes require manual cleanup, limiting accessibility and scalability. Pix2Repair takes an image of the fractured object as input and automatically generates a 3D printable restoration shape. We contribute a novel shape function that deconstructs a latent code representing the fractured object into a complete shape and a break surface. We show restorations for synthetic fractures from the Geometric Breaks and Breaking Bad datasets, and cultural heritage objects from the QP dataset, and for real fractures from the Fantastic Breaks dataset. We overcome challenges in restoring axially symmetric objects by predicting view-centered restorations. Our approach outperforms shape completion approaches adapted for shape repair in terms of chamfer distance, earth mover's distance, normal consistency, and percent restorations generated.