Noam Aigerman
(pronounced "Noh-uhm", like Noah with an M at the end.)
I am a computer scientist working on problems related to 3D and 2D geometry. My research lies at the intersection of geometry processing, computer graphics, deep learning, and optimization.
Currently, I mostly focus on using geometry processing to devise thoeretically-grounded machine learning approaches for 3D problems; and, vice-versa, approaching geometry processing tasks from a machine learning perspective.
Currently, I mostly focus on using geometry processing to devise thoeretically-grounded machine learning approaches for 3D problems; and, vice-versa, approaching geometry processing tasks from a machine learning perspective.

Publications
 
(hover over a project's image for a one-sentence summary)

TextDeformer: Geometry Manipulation using Text Guidance
ACM SIGGRAPH 2023

Neural Face Rigging for Animating and Retargeting Facial Meshes in the Wild
ACM SIGGRAPH 2023

Neural Progressive Meshes
ACM SIGGRAPH 2023
[Coming soon...]

DA Wand: Distortion-Aware Selection using Neural Mesh Parameterization
CVPR 2023

Isometric Energies for Recovering Injectivity in Constrained Mapping
ACM SIGGRAPH Asia 2022

PatchRD: Detail-Preserving Shape Completion by Learning Patch Retrieval and Deformation

Learning Joint Surface Atlases

Neural Jacobian Fields: Learning Intrinsic Mappings of Arbitrary Meshes

Neural Convolutional Surfaces
CVPR 2022

GLASS: Geometric Latent Augmentation for Shape Spaces
CVPR 2022


Optimizing Global Injectivity for Constrained Parameterization
ACM SIGGRAPH ASIA 2021


Swept Volumes via Spacetime Numerical Continuation
ACM SIGGRAPH 2021


Neural Surface Maps
CVPR 2021

Learning Delaunay Surface Elements for Mesh Reconstruction
CVPR 2021 (oral)

Joint Learning of 3D Shape Retrieval and Deformation
CVPR 2021

Developability of Heightfields via Rank Minimization
ACM SIGGRAPH 2020


Lifting Simplices to Find Injectivity
ACM SIGGRAPH 2020

Neural Cages for Detail-Preserving 3D Deformations
CVPR 2020 (oral)

Coupling Explicit and Implicit Surface Representations for Generative 3D Modeling
ECCV 2020


Convolutional Neural Networks on Surfaces via Seamless Toric Covers



Large Scale Bounded Distortion Mappings
ACM SIGGRAPH Asia 2015



Controlling Singular Values with Semidefinite Programming
ACM SIGGRAPH 2014

Injective and Bounded Distortion Mappings in 3D
ACM SIGGRAPH 2013
Others

Computational Aspects of Mappings
Tutorial given at the IGS 2016 summer school (with Shahar Kovalsky)
Slides (pdf)
Slides (pdf)