Yes, this is I! Yes, this is I (in 3D!)
Noam Aigerman Pronounced "Noh-uhm", like Noah with an M at the end.
Research Scientist, Adobe Research
lastname@adobe.com

My research lies within the areas of geometry processing, computer graphics, deep learning, optimization, and the intersection between them.


Publications (hover over a project's image for a one-sentence summary)
    1. 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
    2. 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
    3. 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
    4. 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
    5. 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
    6. 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 Kim, Niloy J. Mitra CVPR 2021
      Project Page
    7. 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
    8. The framework of our method.
      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
    1. 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
    2. 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
    3. 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

    4. 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
    5. 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
    1. 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
    2. 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
    1. 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
    1. 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
    2. 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
    3. 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
    1. 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
    2. 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 (*equal contributors)
      ACM SIGGRAPH 2014
      Paper | Low Res | Project Page
    1. 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)

  1. Others
    1. A deformation of a bar.
      Computational Aspects of Mappings
      Tutorial given at the IGS 2016 summer school (with Shahar Kovalsky)
      Slides (pdf)