Suivre
Souhaib Attaiki
Souhaib Attaiki
Adresse e-mail validée de polytechnique.edu
Titre
Citée par
Citée par
Année
Diffusionnet: Discretization agnostic learning on surfaces
N Sharp, S Attaiki, K Crane, M Ovsjanikov
ACM Transactions on Graphics (TOG) 41 (3), 1-16, 2022
1682022
Dpfm: Deep partial functional maps
S Attaiki, G Pai, M Ovsjanikov
2021 International Conference on 3D Vision (3DV), 175-185, 2021
562021
Understanding and improving features learned in deep functional maps
S Attaiki, M Ovsjanikov
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
102023
SRFeat: Learning locally accurate and globally consistent non-rigid shape correspondence
L Li, S Attaiki, M Ovsjanikov
2022 International Conference on 3D Vision (3DV), 144-154, 2022
102022
NCP: Neural correspondence prior for effective unsupervised shape matching
S Attaiki, M Ovsjanikov
Advances in Neural Information Processing Systems 35, 28842-28857, 2022
82022
DPFM: Deep partial functional maps. In2021 InternationalConference on 3D Vision (3DV)
S Attaiki, G Pai, M Ovsjanikov
IEEE, Dec, 2021
52021
Generalizable local feature pre-training for deformable shape analysis
S Attaiki, L Li, M Ovsjanikov
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
42023
Shape Non-rigid Kinematics (SNK): A Zero-Shot Method for Non-Rigid Shape Matching via Unsupervised Functional Map Regularized Reconstruction
S Attaiki, M Ovsjanikov
Advances in Neural Information Processing Systems 36, 2024
12024
Unsupervised Representation Learning for Diverse Deformable Shape Collections
S Hahner, S Attaiki, J Garcke, M Ovsjanikov
arXiv preprint arXiv:2310.18141, 2023
2023
AtomSurf: Surface Representation for Learning on Protein Structures
V Mallet, S Attaiki, M Ovsjanikov
arXiv preprint arXiv:2309.16519, 2023
2023
Smoothness and effective regularizations in learned embeddings for shape matching
R Marin, S Attaiki, S Melzi, E Rodolà, M Ovsjanikov
arXiv preprint arXiv:2112.07289, 2021
2021
Supplementary Material for: Unsupervised Representation Learning for Diverse Deformable Shape Collections
S Hahner, S Attaiki, J Garcke, M Ovsjanikov
Le système ne peut pas réaliser cette opération maintenant. Veuillez réessayer plus tard.
Articles 1–12