Souhaib Attaiki

Orcid: 0000-0003-4971-8219

According to our database1, Souhaib Attaiki authored at least 14 papers between 2020 and 2025.

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

Timeline

Legend:

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Article 
PhD thesis 
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Links

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Bibliography

2025
GANFusion: Feed-Forward Text-to-3D with Diffusion in GAN Space.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2025

AtomSurf: Surface Representation for Learning on Protein Structures.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024
Robust Deep Learning-based Methods for Non-Rigid Shape Correspondence. (Méthodes Robustes Basées sur l'Apprentissage Profond pour la Correspondance de Formes Non Rigides).
PhD thesis, 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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