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HTTP/2 200 server: GitHub.com content-type: text/html; charset=utf-8 last-modified: Mon, 03 Nov 2025 06:21:37 GMT access-control-allow-origin: * etag: W/"690849f1-16ccb" expires: Sun, 28 Dec 2025 04:54:21 GMT cache-control: max-age=600 content-encoding: gzip x-proxy-cache: MISS x-github-request-id: 1619:2916CC:74774C:825C87:6950B5A4 accept-ranges: bytes age: 0 date: Sun, 28 Dec 2025 04:46:46 GMT via: 1.1 varnish x-served-by: cache-bom-vanm7210072-BOM x-cache: HIT x-cache-hits: 0 x-timer: S1766897206.321370,VS0,VE206 vary: Accept-Encoding x-fastly-request-id: 7fb3f530053d7719d8f9e4f22b0e2b243a5e4789 content-length: 16520 Noam Aigerman's Homepage

Noam Aigerman (pronounced "Noh-uhm", like Noah with an M at the end.)

Associate Professor, University of Montreal
Associate Academic Member, Mila

noam.aigerman@umontreal.ca

Room 3359, André-Aisenstadt building,
C.P. 6128, succ. Centre-Ville,
Montréal, Québec, Canada H3C 3J7

Google Scholar

Bluesky

Calendar

I work on problems related to machine learning and 3D geometry. Namely, my research lies at the intersection of geometry processing, deep learning, and optimization, with applications in 3D vision and computer graphics.
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.

Group

Current:

Zihan Zhu

(PhD, 2025 - )

Tianshu Kuai

(PhD, 2024 - )

Thomas Peschlow

(MSc, 2025 - )

Joey Marten (cosupervised with Prof. Derek Nowrouzezahrai)

(MSc, 2025 - )

Darsh Kaushik

(MSc, 2024 - )

Hongshuo Min

(Undergraduate Intern, 2025)

Alumni:

Martin El Mqirmi

(MSc, 2024 - 2025)

Teaching

Current Year:

IFT6759 - Advanced Machine Learning Projects

(winter 2026)

Past Years:

IFT6095 - Neural Geometry Processing

(winter 2025)

IFT6759 - Advanced Machine Learning Projects

(winter 2025)

IFT6095 - Neural Geometry Processing

(winter 2024)

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

various experiments from the paper: deforming characters to arbitrary poses; segmenting characters; reproducing a high-frequency deformation of a piece of paper.

PoissonNet: A Local-Global Approach for Learning on Surfaces

Arman Maesumi, Tanish Makadia, Thibault Groueix, Vladimir G. Kim, Daniel Ritchie, Noam Aigerman

ACM Transactions on Graphics (SIGGRAPH Asia 2025)

Paper | Project Page | Code

A fluid simulation created using the neural basis.

Neural Kinematic Bases for Fluids

Yibo Liu, Paul Kry, Kenny Erleben, Noam Aigerman, Sune Darkner, Teseo Schneider

ACM SIGGRAPH Asia 2025

Paper | Code (coming soon)

(sorry, not a graphics/vision paper so no pretty images) The core idea of the method: perturbation of the constraint polytopes leads to a perturbation of the solution, while non-active constraints can be ignored.

Differentiation Through Black-Box Quadratic Programming Solvers

Connor W. Magoon, Fengyu Yang, Noam Aigerman, Shahar Z. Kovalsky

NeurIPS 2025

Paper | Code

Bottom row: a model viewed from varying viewpoints does not fit the target sketch (bottom left, red); our method enables deform the model to fit to the sketch (top left) while still appearing the same as before from other views (top row).

View-Dependent Deformation Fields for 2D Editing of 3D Models

Martin El Mqirmi, Noam Aigerman

ACM/EG Expressive Symposium 2025

Paper | Code | Project Page

A 3D model of a bear is kept intact while adding wings (guided by a text prompt), by masking part of the object (purple ellipsoid) and reconstructing that part.

Instant3dit: Multiview Inpainting for Fast Editing of 3D Objects

Amir Barda, Matheus Gadelha, Vladimir G. Kim, Noam Aigerman, Amit Haim Bermano, Thibault Groueix

CVPR 2025

Paper | Project Page

A wolf automatically deformed to a hipo via text-guided deformation.

MeshUp: Multi-Target Mesh Deformation via Blended Score Distillation

Hyunwoo Kim, Itai Lang, Thibault Groueix, Noam Aigerman, Vladimir G. Kim, Rana Hanocka

3DV 2025 (best paper runnerup)

Paper | Project Page

A horse reconstructed from a point cloud, using our method.

Temporally-Consistent Surface Reconstruction using Metrically-Consistent Atlases

Jan Bednarik, Noam Aigerman, Vladimir G. Kim, Siddhartha Chaudhuri, Shaifali Parashar, Mathieu Salzmann, Pascal Fua

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2025

Paper | Code

A chosen region on the back of the armadillo is deformed to different types of wings, based on different input text prompts.

MagicClay: Sculpting Meshes With Generative Neural Fields

Amir Barda, Vladimir Kim, Noam Aigerman, Amit Haim Bermano, Thibault Groueix

ACM SIGGRAPH Asia 2024

Paper | Project Page

A coarse shape is added local details based on the details of five chosen fine shapes.

DECOLLAGE: 3D Detailization by Controllable, Localized, and Learned Geometry Enhancement

Qimin Chen, Zhiqin Chen, Vladimir G. Kim, Noam Aigerman, Hao Zhang, Siddhartha Chaudhuri

ECCV 2024

Paper | Project Page

Two different models, animated by our method

Temporal Residual Jacobians for Rig-free Motion Transfer

Sanjeev Muralikrishnan, Niladri Shekhar Dutt, Siddhartha Chaudhuri, Noam Aigerman, Vladimir Kim, Matthew Fisher, Niloy Mitra

ECCV 2024

Paper | Project Page

Four tilings of the plane automatically generated by our method, for four different symmetry patterns containing rotations and reflections, and four different prompts ('Flamenco dancer', 'Ballet dancer', 'Alligator', 'Unicorn').

Generative Escher Meshes

Noam Aigerman, Thibault Groueix

ACM SIGGRAPH 2024

Paper | Code

An extreme elastic deformation of a NeRF, without any visual artifacts as the deformation is guaranteed to be 1-to-1.

TutteNet: Injective 3D Deformations by Composition of 2D Mesh Deformations

Bo Sun, Thibault Groueix, Chen Song, Qixing Huang, Noam Aigerman

CVPR 2024

Paper | Code

A 1-to-1 map between two 3D models which respects semantic correspondence, computed automatically using our method. Map is visualized by placing a checker texture on the left mesh and using the map to transfer the texture to the right mesh.

Neural Semantic Surface Maps

Luca Morreale, Noam Aigerman, Vladimir G. Kim, Niloy Mitra

Computer Graphics Forum (Eurographics 2024)

Project page

Top: point clouds are generated through a pretrained generative model, and are used to deform and swap meshes (bottom).

Explorable Mesh Deformation Subspaces from Unstructured 3D Generative Models

Arman Maesumi, Paul Guerrero, Vladimir G. Kim, Matthew Fisher, Siddhartha Chaudhuri, Noam Aigerman, Daniel Ritchie

ACM SIGGRAPH Asia 2023

Project page

The cow is deformed into two desired shapes described by a text prompt, in this case a turtle and a stag.

TextDeformer: Geometry Manipulation using Text Guidance

William Gao, Noam Aigerman, Thibault Groueix, Vladimir G. Kim, Rana Hanocka

ACM SIGGRAPH 2023

Project page

Face meshes from various datasets, with different triangulations, can be automatically deformed by our network into two facial expressions.

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

Dafei Qin, Jun Saito, Noam Aigerman, Thibault Groueix, Taku Komura

ACM SIGGRAPH 2023

Paper

A coarse mesh is progressively refined using a neural network, given additional details transmitted.

Neural Progressive Meshes

Yun-Chun Chen, Vladimir G. Kim, Noam Aigerman, Alec Jacobson

ACM SIGGRAPH 2023

Paper

A point is selected on the mesh by a user, and a region containing this point is selected by our network, such that the region can UV-mapped with low-distortion (UV map visualized with a square texture on the selected region).

DA Wand: Distortion-Aware Selection using Neural Mesh Parameterization

Richard Liu, Noam Aigerman, Vladimir G. Kim, Rana Hanocka

CVPR 2023

Paper | Project page

Multiple axis of symmetry detected on a 3D object, using a proximal operator.

Learning Proximal Operators to Discover Multiple Optima

Lingxiao Li, Noam Aigerman, Vladimir G. Kim, Jiajin Li, Kristjan Greenewald, Mikhail Yurochkin, Justin Solomon

ICLR 2023

Paper | Code

Top: our previous method can produce a 1-to-1 UV map of the bunny into the cross, but has distortion and scales some parts of mesh (in red). Bottom: this paper can also compute a 1-to-1 UV map, but also ensure it has low distortion and less scaling.

Isometric Energies for Recovering Injectivity in Constrained Mapping

Xingyi Du, Danny M. Kaufman, Qingnan Zhou, Shahar Z. Kovalsky, Yajie Yan, Noam Aigerman, Tao Ju

ACM SIGGRAPH Asia 2022

Project page

A chair with parts of it missing (left) is completed by our method to a full chair (middle) by copying and transforming existing parts to missing areas, while competing generative approaches produce fuzzy approximiations (right).

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

Bo Sun, Vladimir G. Kim, Noam Aigerman, Qixing Huang, Siddhartha Chaudhuri

ECCV 2022

Paper | Code

Our method produces an atlas with a complex topology for a set of shapes.

Learning Joint Surface Atlases

Theo Deprelle, Thibault Groueix, Noam Aigerman, Vladimir G. Kim, Mathieu Aubry

ECCV Workshop on Learning to Generate 3D Shapes and Scenes, 2022

Paper | Code

left: a UV map predicted by the network, almost identical to the ground-truth. Right: the network correctly reposes the bunny to the poses demonstrated by the human.

Neural Jacobian Fields: Learning Intrinsic Mappings of Arbitrary Meshes

Noam Aigerman, Kunal Gupta, Vladimir G. Kim, Siddhartha Chaudhuri, Jun Saito, Thibault Groueix

ACM SIGGRAPH 2022 (journal track)

Paper | Code

A diagram of our spherical convolution operator.

Mobius Convolutions for Spherical CNNs

Thomas Mitchel, Noam Aigerman, Vladimir G. Kim, Michael Kazhdan

ACM SIGGRAPH 2022

Paper | Code

The framework learns to represent a surface map from a coarse atlasnet-like MLP composed with a CNN that adds details

Neural Convolutional Surfaces

Luca Morreale, Noam Aigerman, Paul Guerrero, Vladimir G. Kim, Niloy Mitra

CVPR 2022

Project Page

Various poses (orange) generated by our method from a few landmark poses (gray).

GLASS: Geometric Latent Augmentation for Shape Spaces

Sanjeev Muralikrishnan, Siddhartha Chaudhuri, Noam Aigerman, Vladimir G. Kim, Matthew Fisher, Niloy Mitra

CVPR 2022

Paper

A mesh (right) generated by optimizing the alignment of its edges to the input vector field (left).

Differentiable Surface Triangulation

Marie-Julie Rakotosaona, Noam Aigerman, Niloy Mitra, Maks Ovsjanikov, Paul Guerrero

ACM SIGGRAPH ASIA 2021

Paper | Code

A mesh (left) is paramterized to an initial parameterization (middle) with local inversions of triangles and global overlaps of the boundary, which are then alleviated through our optimization (right).

Optimizing Global Injectivity for Constrained Parameterization

Xingyi Du, Danny M. Kaufman, Qingnan Zhou, Shahar Z. Kovalsky, Yajie Yan, Noam Aigerman, Tao Ju

ACM SIGGRAPH ASIA 2021

Project Page

A sequence of reconstructed surfaces using our algorithm, exhibiting good consistent correspondences between each frame in the sequence them (visualized via texture that exhibits the correspondence).

Temporally-Coherent Surface Reconstruction via Metric-Consistent Atlases

Jan Bednarik, Vladimir G. Kim, Siddhartha Chaudhuri, Shaifali Parashar, Mathieu Salzmann, Pascal Fua, Noam Aigerman

ICCV 2021

Paper | Video

A 2D brush is swept along a spiraling trajectory (left), tracing the golden horn (right).

Swept Volumes via Spacetime Numerical Continuation

Silvia Sellán, Noam Aigerman, Alec Jacobson

ACM SIGGRAPH 2021

Project Page

Coarse voxel grids (red) are refined into different types of plants (yellow), based on the input desired style (green).

DECOR-GAN: 3D Shape Detailization by Conditional Refinement

Zhiqin Chen, Vladimir G. Kim, Matthew Fisher, Noam Aigerman, Hao Zhang, Siddhartha Chaudhuri

CVPR 2021 (oral)

Paper | Code

Two surfaces are repsented as 2D-to-3D maps via two overfitted neural networks. Since they are both differentiable,this in turn enables optimizing a surface-to-surface map (via h) in a completely differentiable manner.

Neural Surface Maps

Luca Morreale, Noam Aigerman, Vladimir G. Kim, Niloy J. Mitra

CVPR 2021

Project Page

A point cloud is meshed using our neural network.

Learning Delaunay Surface Elements for Mesh Reconstruction

Marie-Julie Rakotosaona, Paul Guerrero, Noam Aigerman, Niloy J. Mitra, Maks Ovsjanikov

CVPR 2021 (oral)

Project Page

Joint Learning of 3D Shape Retrieval and Deformation

Mikaela Angelina Uy, Vladimir G. Kim, Minhyuk Sung, Noam Aigerman, Siddhartha Chaudhuri, Leonidas Guibas

CVPR 2021

Project Page

Our method approximates the input heightfield surface (left) by a piecewise-developable heightfield surface (right).

Developability of Heightfields via Rank Minimization

Silvia Sellán, Noam Aigerman, Alec Jacobson

ACM SIGGRAPH 2020

Project Page

A coarse mesh is subidivided via a neural network, which restores natural geometric features without over-smoothing.

Neural Subdivision

Hsueh-Ti Derek Liu, Vladimir G. Kim, Siddhartha Chaudhuri, Noam Aigerman, Alec Jacobson

ACM SIGGRAPH 2020

Paper | Code

Mapping a mesh into a non-convex domain without any inversions, yielding a globally injective map

Lifting Simplices to Find Injectivity

Xingyi Du, Noam Aigerman, Qingnan Zhou, Shahar Kovalsky, Yajie Yan, Danny M. Kaufman, Tao Ju

ACM SIGGRAPH 2020

Paper | Project Page | Code | Data Set | Video

Deforming humanoids to match example poses via a neural network, while preserving details.

Neural Cages for Detail-Preserving 3D Deformations

Wang Yifan, Noam Aigerman, Vladimir G. Kim, Siddhartha Chaudhuri, Olga Sorkine-Hornung

CVPR 2020 (oral)

Paper | Project Page

Comparison of reconstruction quality of the hybrid reconstruction versus the two components of the hybrid.

Coupling Explicit and Implicit Surface Representations for Generative 3D Modeling

Omid Poursaeed, Matthew Fisher, Noam Aigerman, Vladimir G. Kim

ECCV 2020

Project Page

An embedding of a mesh into a spherical orbifold, which can tile the sphere.

Spherical Orbifold Tutte Embeddings

Noam Aigerman, Shahar Kovalsky, Yaron Lipman

ACM SIGGRAPH 2017

Paper | Low Res | Code

A convolution of a filter on a spherical surface is well-defined on the surface's toric 4-cover.

Convolutional Neural Networks on Surfaces via Seamless Toric Covers

Haggai Maron, Meirav Galun, Noam Aigerman, Miri Trope, Nadav Dym, Ersin Yumer, Vladimir G. Kim, Yaron Lipman

ACM SIGGRAPH 2017

Paper | Low Res | Code

An embedding of a mesh into a hyperbolic orbifold, which can tile the Poincare-disk model of the hyperbolic plane.

Hyperbolic Orbifold Tutte Embeddings

Noam Aigerman, Yaron Lipman

ACM SIGGRAPH Asia 2016

Paper | Low Res | Code

An embedding of a mesh into a planar orbifold, which can also be used to generate seamless quads on the mesh.

Orbifold Tutte Embeddings

Noam Aigerman, Yaron Lipman

ACM SIGGRAPH Asia 2015

Paper | Low Res | Code

A large-scale bijective parametrization of a tetrahedral mesh to a ball.

Large Scale Bounded Distortion Mappings

Shahar Kovalsky, Noam Aigerman, Ronen Basri, Yaron Lipman

ACM SIGGRAPH Asia 2015

Paper | Low Res | Project Page

Two identical bijective maps between two surface-meshes produced for two different cut placements.

Seamless Surface Mappings

Noam Aigerman, Roi Poranne, Yaron Lipman

ACM SIGGRAPH 2015

Paper | Low Res

A low distortion bijective map between two surface-meshes.

Lifted Bijections for Low Distortion Surface Mappings

Noam Aigerman, Roi Poranne, Yaron Lipman

ACM SIGGRAPH 2014

Paper | Low Res

The 'most conformal' mapping of a volumetric cube, subject to repositioning its eight corners.

Controlling Singular Values with Semidefinite Programming

Shahar Kovalsky, Noam Aigerman, Ronen Basri, Yaron Lipman

ACM SIGGRAPH 2014

Paper | Low Res | Project Page

A bounded-distortion, globally bijective map, mapping a tetrahedral mesh to a polycube.

Injective and Bounded Distortion Mappings in 3D

Noam Aigerman, Yaron Lipman

ACM SIGGRAPH 2013

Paper | Low Res | Project Page (code + data)

Research, in a nutshell

Original Source | Taken Source