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08/28/2023
VoroMesh: Learning Watertight Surface Meshes with Voronoi Diagrams
In stark contrast to the case of images, finding a concise, learnable di...
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08/17/2023
Spatially and Spectrally Consistent Deep Functional Maps
Cycle consistency has long been exploited as a powerful prior for jointl...
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06/05/2023
Zero-Shot 3D Shape Correspondence
We propose a novel zero-shot approach to computing correspondences betwe...
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04/11/2023
SATR: Zero-Shot Semantic Segmentation of 3D Shapes
We explore the task of zero-shot semantic segmentation of 3D shapes by u...
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03/29/2023
Understanding and Improving Features Learned in Deep Functional Maps
Deep functional maps have recently emerged as a successful paradigm for ...
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03/27/2023
Generalizable Local Feature Pre-training for Deformable Shape Analysis
Transfer learning is fundamental for addressing problems in settings wit...
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03/10/2023
Scalable and Efficient Functional Map Computations on Dense Meshes
Spectral geometric methods have brought revolutionary changes to the fie...
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01/14/2023
NCP: Neural Correspondence Prior for Effective Unsupervised Shape Matching
We present Neural Correspondence Prior (NCP), a new paradigm for computi...
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12/05/2022
TIDE: Time Derivative Diffusion for Deep Learning on Graphs
A prominent paradigm for graph neural networks is based on the message p...
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11/29/2022
Equivalence Between SE(3) Equivariant Networks via Steerable Kernels and Group Convolution
A wide range of techniques have been proposed in recent years for design...
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11/26/2022
Reduced Representation of Deformation Fields for Effective Non-rigid Shape Matching
In this work we present a novel approach for computing correspondences b...
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10/12/2022
Learning Multi-resolution Functional Maps with Spectral Attention for Robust Shape Matching
In this work, we present a novel non-rigid shape matching framework base...
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10/05/2022
Smooth Non-Rigid Shape Matching via Effective Dirichlet Energy Optimization
We introduce pointwise map smoothness via the Dirichlet energy into the ...
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10/04/2022
Affection: Learning Affective Explanations for Real-World Visual Data
In this work, we explore the emotional reactions that real-world images ...
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09/16/2022
SRFeat: Learning Locally Accurate and Globally Consistent Non-Rigid Shape Correspondence
In this work, we present a novel learning-based framework that combines ...
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05/10/2022
Non-Isometric Shape Matching via Functional Maps on Landmark-Adapted Bases
We propose a principled approach for non-isometric landmark-preserving n...
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04/28/2022
Deep Orientation-Aware Functional Maps: Tackling Symmetry Issues in Shape Matching
State-of-the-art fully intrinsic networks for non-rigid shape matching o...
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03/15/2022
Implicit field supervision for robust non-rigid shape matching
Establishing a correspondence between two non-rigidly deforming shapes i...
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12/17/2021
Complex Functional Maps : a Conformal Link Between Tangent Bundles
In this paper, we introduce complex functional maps, which extend the fu...
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12/14/2021
Why you should learn functional basis
Efficient and practical representation of geometric data is a ubiquitous...
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12/05/2021
Joint Symmetry Detection and Shape Matching for Non-Rigid Point Cloud
Despite the success of deep functional maps in non-rigid 3D shape matchi...
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10/19/2021
DPFM: Deep Partial Functional Maps
We consider the problem of computing dense correspondences between non-r...
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10/06/2021
Learning Canonical Embedding for Non-rigid Shape Matching
This paper provides a novel framework that learns canonical embeddings f...
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09/22/2021
Differentiable Surface Triangulation
Triangle meshes remain the most popular data representation for surface ...
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09/16/2021
Intuitive and Efficient Roof Modeling for Reconstruction and Synthesis
We propose a novel and flexible roof modeling approach that can be used ...
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08/05/2021
UPDesc: Unsupervised Point Descriptor Learning for Robust Registration
In this work, we propose UPDesc, an unsupervised method to learn point d...
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03/31/2021
Spectral Unions of Partial Deformable 3D Shapes
Spectral geometric methods have brought revolutionary changes to the fie...
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02/05/2021
Matrix Decomposition on Graphs: A Functional View
We propose a functional view of matrix decomposition problems on graphs ...
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01/19/2021
ArtEmis: Affective Language for Visual Art
We present a novel large-scale dataset and accompanying machine learning...
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12/02/2020
Learning Delaunay Surface Elements for Mesh Reconstruction
We present a method for reconstructing triangle meshes from point clouds...
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12/01/2020
DiffusionNet: Discretization Agnostic Learning on Surfaces
We introduce a new approach to deep learning on 3D surfaces, based on th...
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10/25/2020
Correspondence Learning via Linearly-invariant Embedding
In this paper, we propose a fully differentiable pipeline for estimating...
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09/30/2020
Structured Regularization of Functional Map Computations
We consider the problem of non-rigid shape matching using the functional...
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09/29/2020
Geometric Matrix Completion: A Functional View
We propose a totally functional view of geometric matrix completion prob...
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09/28/2020
Weakly Supervised Deep Functional Map for Shape Matching
A variety of deep functional maps have been proposed recently, from full...
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06/01/2020
MapTree: Recovering Multiple Solutions in the Space of Maps
In this paper we propose an approach for computing multiple high-quality...
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04/03/2020
Intrinsic Point Cloud Interpolation via Dual Latent Space Navigation
We present a learning-based method for interpolating and manipulating 3D...
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03/31/2020
Deep Geometric Functional Maps: Robust Feature Learning for Shape Correspondence
We present a novel learning-based approach for computing correspondences...
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03/14/2020
Instant recovery of shape from spectrum via latent space connections
We introduce the first learning-based method for recovering shapes from ...
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06/27/2019
Effective Rotation-invariant Point CNN with Spherical Harmonics kernels
We present a novel rotation invariant architecture operating directly on...
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06/14/2019
Correspondence-Free Region Localization for Partial Shape Similarity via Hamiltonian Spectrum Alignment
We consider the problem of localizing relevant subsets of non-rigid geom...
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05/08/2019
Spectral Coarsening of Geometric Operators
We introduce a novel approach to measure the behavior of a geometric ope...
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04/24/2019
OperatorNet: Recovering 3D Shapes From Difference Operators
This paper proposes a learning-based framework for reconstructing 3D sha...
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04/16/2019
ZoomOut: Spectral Upsampling for Efficient Shape Correspondence
We present a simple and efficient method for refining maps or correspond...
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01/04/2019
POINTCLEANNET: Learning to Denoise and Remove Outliers from Dense Point Clouds
Point clouds obtained with 3D scanners or by image-based reconstruction ...
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12/10/2018
Unsupervised Deep Learning for Structured Shape Matching
We present a novel method for computing correspondences across shapes us...
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11/28/2018
Isospectralization, or how to hear shape, style, and correspondence
The question whether one can recover the shape of a geometric object fro...
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10/01/2018
Multi-directional Geodesic Neural Networks via Equivariant Convolution
We propose a novel approach for performing convolution of signals on cur...
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06/12/2018
Continuous and Orientation-preserving Correspondences via Functional Maps
We propose a method for efficiently computing orientation-preserving and...
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06/11/2018