Souhaib Attaiki

22 papers A* 5A 1Journal 12Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	AtomSurf: Surface Representation for Learning on Protein Structures. ICLR Vincent Mallet, Yangyang Miao, Souhaib Attaiki, Bruno Correia, Maks Ovsjanikov
2025	A	`conf`	GANFusion: Feed-Forward Text-to-3D with Diffusion in GAN Space. WACV Souhaib Attaiki, Paul Guerrero, Duygu Ceylan, Niloy J. Mitra, Maks Ovsjanikov
2024	J	`jnl`	GANFusion: Feed-Forward Text-to-3D with Diffusion in GAN Space. CoRR Souhaib Attaiki, Paul Guerrero, Duygu Ceylan, Niloy J. Mitra, Maks Ovsjanikov
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). Souhaib Attaiki
2024	J	`jnl`	Shape Non-rigid Kinematics (SNK): A Zero-Shot Method for Non-Rigid Shape Matching via Unsupervised Functional Map Regularized Reconstruction. CoRR Souhaib Attaiki, Maks Ovsjanikov
2024	—	`conf`	Unsupervised Representation Learning for Diverse Deformable Shape Collections. 3DV Sara Hahner, Souhaib Attaiki, Jochen Garcke, Maks Ovsjanikov
2023	J	`jnl`	AtomSurf : Surface Representation for Learning on Protein Structures. CoRR Vincent Mallet, Souhaib Attaiki, Maks Ovsjanikov
2023	A*	`conf`	Generalizable Local Feature Pre-training for Deformable Shape Analysis. CVPR Souhaib Attaiki, Lei Li, Maks Ovsjanikov
2023	J	`jnl`	Generalizable Local Feature Pre-training for Deformable Shape Analysis. CoRR Souhaib Attaiki, Lei Li, Maks Ovsjanikov
2023	J	`jnl`	NCP: Neural Correspondence Prior for Effective Unsupervised Shape Matching. CoRR Souhaib Attaiki, Maks Ovsjanikov
2023	A*	`conf`	Shape Non-rigid Kinematics (SNK): A Zero-Shot Method for Non-Rigid Shape Matching via Unsupervised Functional Map Regularized Reconstruction. NeurIPS Souhaib Attaiki, Maks Ovsjanikov
2023	A*	`conf`	Understanding and Improving Features Learned in Deep Functional Maps. CVPR Souhaib Attaiki, Maks Ovsjanikov
2023	J	`jnl`	Understanding and Improving Features Learned in Deep Functional Maps. CoRR Souhaib Attaiki, Maks Ovsjanikov
2023	J	`jnl`	Unsupervised Representation Learning for Diverse Deformable Shape Collections. CoRR Sara Hahner, Souhaib Attaiki, Jochen Garcke, Maks Ovsjanikov
2022	J	`jnl`	DiffusionNet: Discretization Agnostic Learning on Surfaces. ACM Trans. Graph. Nicholas Sharp, Souhaib Attaiki, Keenan Crane, Maks Ovsjanikov
2022	A*	`conf`	NCP: Neural Correspondence Prior for Effective Unsupervised Shape Matching. NeurIPS Souhaib Attaiki, Maks Ovsjanikov
2022	—	`conf`	SRFeat: Learning Locally Accurate and Globally Consistent Non-Rigid Shape Correspondence. 3DV Lei Li, Souhaib Attaiki, Maks Ovsjanikov
2022	J	`jnl`	SRFeat: Learning Locally Accurate and Globally Consistent Non-Rigid Shape Correspondence. CoRR Lei Li, Souhaib Attaiki, Maks Ovsjanikov
2021	—	`conf`	DPFM: Deep Partial Functional Maps. 3DV Souhaib Attaiki, Gautam Pai, Maks Ovsjanikov
2021	J	`jnl`	DPFM: Deep Partial Functional Maps. CoRR Souhaib Attaiki, Gautam Pai, Maks Ovsjanikov
2021	J	`jnl`	Why you should learn functional basis. CoRR Riccardo Marin, Souhaib Attaiki, Simone Melzi, Emanuele Rodolà, Maks Ovsjanikov
2020	J	`jnl`	Diffusion is All You Need for Learning on Surfaces. CoRR Nicholas Sharp, Souhaib Attaiki, Keenan Crane, Maks Ovsjanikov