704 citations · 3.6k across the 98 of their papers we have counts for
10 papers · 1 filter
SENS: Part-Aware Sketch-based Implicit Neural Shape Modeling
Alexandre Binninger, Amir Hertz, Olga Sorkine-Hornung +2
We present SENS, a novel method for generating and editing 3D models from hand-drawn sketches, including those of abstract nature. Our method allows users to quickly and easily ske…
SPAGHETTI: Editing Implicit Shapes Through Part Aware Generation
Amir Hertz, Or Perel, Raja Giryes +2
Neural implicit fields are quickly emerging as an attractive representation for learning based techniques. However, adopting them for 3D shape modeling and editing is challenging.…
NeuralMLS: Geometry-Aware Control Point Deformation
Meitar Shechter, Rana Hanocka, Gal Metzer +2
We introduce NeuralMLS, a space-based deformation technique, guided by a set of displaced control points. We leverage the power of neural networks to inject the underlying shape ge…
Mesh Draping: Parametrization-Free Neural Mesh Transfer
Amir Hertz, Or Perel, Raja Giryes +2
Despite recent advances in geometric modeling, 3D mesh modeling still involves a considerable amount of manual labor by experts. In this paper, we introduce Mesh Draping: a neural…
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…
Z2P: Instant Visualization of Point Clouds
Gal Metzer, Rana Hanocka, Raja Giryes +2
We present a technique for visualizing point clouds using a neural network. Our technique allows for an instant preview of any point cloud, and bypasses the notoriously difficult s…
Self-Sampling for Neural Point Cloud Consolidation
Gal Metzer, Rana Hanocka, Raja Giryes +1
We introduce a novel technique for neural point cloud consolidation which learns from only the input point cloud. Unlike other point upsampling methods which analyze shapes via loc…
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…
ALIGNet: Partial-Shape Agnostic Alignment via Unsupervised Learning
Rana Hanocka, Noa Fish, Zhenhua Wang +3
The process of aligning a pair of shapes is a fundamental operation in computer graphics. Traditional approaches rely heavily on matching corresponding points or features to guide…