Gautam Pai

According to our database, Gautam Pai authored at least 20 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Geodesic Tracking via New Data-Driven Connections of Cartan Type for Vascular Tree Tracking.

Nick J. van de Berg, Bart M. N. Smets, Gautam Pai, Jean-Marie Mirebeau, Remco Duits

J. Math. Imaging Vis., April, 2024

Deep Learning for Segmentation of Cracks in High-Resolution Images of Steel Bridges.

Andrii Kompanets, Gautam Pai, Remco Duits, Davide Leonetti, Bert Snijder

CoRR, 2024

Optimal Transport on the Lie Group of Roto-translations.

Daan L. J. Bon, Gautam Pai, Gijs Bellaard, Olga Mula, Remco Duits

CoRR, 2024

2023

Analysis of (sub-)Riemannian PDE-G-CNNs.

Gijs Bellaard, Daan L. J. Bon, Gautam Pai, Bart M. N. Smets, Remco Duits

J. Math. Imaging Vis., December, 2023

Geometric Adaptations of PDE-G-CNNs.

Gijs Bellaard, Gautam Pai, Javier Oliván Bescós, Remco Duits

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2023

Functional Properties of PDE-Based Group Equivariant Convolutional Neural Networks.

Gautam Pai, Gijs Bellaard, Bart M. N. Smets, Remco Duits

Proceedings of the Geometric Science of Information - 6th International Conference, 2023

2022

Deep Isometric Maps.

Gautam Pai, Alex M. Bronstein, Ronen Talmon, Ron Kimmel

Image Vis. Comput., 2022

Implicit Field Supervision for Robust Non-rigid Shape Matching.

Ramana Sundararaman, Gautam Pai, Maks Ovsjanikov

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

Fast Sinkhorn Filters: Using Matrix Scaling for Non-Rigid Shape Correspondence With Functional Maps.

Gautam Pai, Jing Ren, Simone Melzi, Peter Wonka, Maks Ovsjanikov

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

DPFM: Deep Partial Functional Maps.

Souhaib Attaiki, Gautam Pai, Maks Ovsjanikov

Proceedings of the International Conference on 3D Vision, 2021

2020

A modified Allen-Cahn model for pattern synthesis on surfaces.

Lorina Dascal, Gautam Pai, Ron Kimmel

CoRR, 2020

2019

Learning for Numerical Geometry.

Gautam Pai

PhD thesis, 2019

Bilateral Operators for Functional Maps.

Gautam Pai, Mor Joseph-Rivlin, Ron Kimmel

CoRR, 2019

DIMAL: Deep Isometric Manifold Learning Using Sparse Geodesic Sampling.

Gautam Pai, Ronen Talmon, Alexander M. Bronstein, Ron Kimmel

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2019

Deep Eikonal Solvers.

Moshe Lichtenstein, Gautam Pai, Ron Kimmel

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2019

2018

Sparse Approximation of 3D Meshes Using the Spectral Geometry of the Hamiltonian Operator.

Yoni Choukroun, Gautam Pai, Ron Kimmel

J. Math. Imaging Vis., 2018

2017

Parametric Manifold Learning Via Sparse Multidimensional Scaling.

Gautam Pai, Ronen Talmon, Ron Kimmel

CoRR, 2017

Schrödinger Operator for Sparse Approximation of 3D Meshes.

Yoni Choukroun, Gautam Pai, Ron Kimmel

Proceedings of the 15th Eurographics Symposium on Geometry Processing, 2017

Learning Invariant Representations Of Planar Curves.

Gautam Pai, Aaron Wetzler, Ron Kimmel

Proceedings of the 5th International Conference on Learning Representations, 2017

2015

Symmetric Smoothing Filters From Global Consistency Constraints.

Sheikh Mohammadul Haque, Gautam P. Pai, Venu Madhav Govindu

IEEE Trans. Image Process., 2015