Souhaib Attaiki

According to our database, Souhaib Attaiki authored at least 11 papers between 2020 and 2023.

Collaborative distances:

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

2023

Unsupervised Representation Learning for Diverse Deformable Shape Collections.

Sara Hahner, Souhaib Attaiki, Jochen Garcke, Maks Ovsjanikov

CoRR, 2023

AtomSurf : Surface Representation for Learning on Protein Structures.

Vincent Mallet, Souhaib Attaiki, Maks Ovsjanikov

CoRR, 2023

Shape Non-rigid Kinematics (SNK): A Zero-Shot Method for Non-Rigid Shape Matching via Unsupervised Functional Map Regularized Reconstruction.

Souhaib Attaiki, Maks Ovsjanikov

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Understanding and Improving Features Learned in Deep Functional Maps.

Souhaib Attaiki, Maks Ovsjanikov

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Generalizable Local Feature Pre-training for Deformable Shape Analysis.

Souhaib Attaiki, Lei Li, Maks Ovsjanikov

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

DiffusionNet: Discretization Agnostic Learning on Surfaces.

Nicholas Sharp, Souhaib Attaiki, Keenan Crane, Maks Ovsjanikov

ACM Trans. Graph., 2022

NCP: Neural Correspondence Prior for Effective Unsupervised Shape Matching.

Souhaib Attaiki, Maks Ovsjanikov

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

SRFeat: Learning Locally Accurate and Globally Consistent Non-Rigid Shape Correspondence.

Lei Li, Souhaib Attaiki, Maks Ovsjanikov

Proceedings of the International Conference on 3D Vision, 2022

2021

Why you should learn functional basis.

Riccardo Marin, Souhaib Attaiki, Simone Melzi, Emanuele Rodolà, Maks Ovsjanikov

CoRR, 2021

DPFM: Deep Partial Functional Maps.

Souhaib Attaiki, Gautam Pai, Maks Ovsjanikov

Proceedings of the International Conference on 3D Vision, 2021

2020

Diffusion is All You Need for Learning on Surfaces.

Nicholas Sharp, Souhaib Attaiki, Keenan Crane, Maks Ovsjanikov

CoRR, 2020