235 citations · 290 across the 2 of their papers we have counts for
7 papers
Orienting Point Clouds with Dipole Propagation
Gal Metzer, Rana Hanocka, Denis Zorin +3
Establishing a consistent normal orientation for point clouds is a notoriously difficult problem in geometry processing, requiring attention to both local and global shape characte…
Deep Geometric Texture Synthesis
Amir Hertz, Rana Hanocka, Raja Giryes +1
Recently, deep generative adversarial networks for image generation have advanced rapidly; yet, only a small amount of research has focused on generative models for irregular struc…
Point2Mesh: A Self-Prior for Deformable Meshes
Rana Hanocka, Gal Metzer, Raja Giryes +1
In this paper, we introduce Point2Mesh, a technique for reconstructing a surface mesh from an input point cloud. Instead of explicitly specifying a prior that encodes the expected…
PointGMM: a Neural GMM Network for Point Clouds
Amir Hertz, Rana Hanocka, Raja Giryes +1
Point clouds are a popular representation for 3D shapes. However, they encode a particular sampling without accounting for shape priors or non-local information. We advocate for th…
Blind Visual Motif Removal from a Single Image
Amir Hertz, Sharon Fogel, Rana Hanocka +2
Many images shared over the web include overlaid objects, or visual motifs, such as text, symbols or drawings, which add a description or decoration to the image. For example, deco…
MeshCNN: A Network with an Edge
Rana Hanocka, Amir Hertz, Noa Fish +3
Polygonal meshes provide an efficient representation for 3D shapes. They explicitly capture both shape surface and topology, and leverage non-uniformity to represent large flat reg…