We provide a novel approach to perform fully automated generation of restorations for fractured shapes using learned implicit shape representations in the form of occupancy functions. Our approach lays the groundwork to ...

We present PRIFIT, a semi-supervised approach for label-efficient learning of 3D point cloud segmentation networks. PRIFIT combines geometric primitive fitting with point-based representation learning. Its key idea is to ...

We present a StyleGAN2-based deep learning approach for 3D shape generation, called SDF-StyleGAN, with the aim of reducing visual and geometric dissimilarity between generated shapes and a shape collection. We extend ...