Souhaib Attaiki

Orcid: 0000-0003-4971-8219

According to our database1, Souhaib Attaiki authored at least 11 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Unsupervised Representation Learning for Diverse Deformable Shape Collections.
Proceedings of the International Conference on 3D Vision, 2024

2023
AtomSurf : Surface Representation for Learning on Protein Structures.
CoRR, 2023

Shape Non-rigid Kinematics (SNK): A Zero-Shot Method for Non-Rigid Shape Matching via Unsupervised Functional Map Regularized Reconstruction.
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.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Generalizable Local Feature Pre-training for Deformable Shape Analysis.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
DiffusionNet: Discretization Agnostic Learning on Surfaces.
ACM Trans. Graph., 2022

NCP: Neural Correspondence Prior for Effective Unsupervised Shape Matching.
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.
Proceedings of the International Conference on 3D Vision, 2022

2021
Why you should learn functional basis.
CoRR, 2021

DPFM: Deep Partial Functional Maps.
Proceedings of the International Conference on 3D Vision, 2021

2020
Diffusion is All You Need for Learning on Surfaces.
CoRR, 2020


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