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ORCIDSouhaib Attaiki
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2020 – today
- 2024
[c7]Sara Hahner, Souhaib Attaiki, Jochen Garcke, Maks Ovsjanikov:
Unsupervised Representation Learning for Diverse Deformable Shape Collections. 3DV 2024: 1594-1604- [i11]Souhaib Attaiki, Maks Ovsjanikov:
Shape Non-rigid Kinematics (SNK): A Zero-Shot Method for Non-Rigid Shape Matching via Unsupervised Functional Map Regularized Reconstruction. CoRR abs/2403.06804 (2024) - [i10]Souhaib Attaiki, Paul Guerrero, Duygu Ceylan, Niloy J. Mitra, Maks Ovsjanikov:
GANFusion: Feed-Forward Text-to-3D with Diffusion in GAN Space. CoRR abs/2412.16717 (2024) - 2023
- [c6]Souhaib Attaiki, Maks Ovsjanikov:
Understanding and Improving Features Learned in Deep Functional Maps. CVPR 2023: 1316-1326 - [c5]Souhaib Attaiki, Lei Li, Maks Ovsjanikov:
Generalizable Local Feature Pre-training for Deformable Shape Analysis. CVPR 2023: 13650-13661 - [c4]Souhaib Attaiki, Maks Ovsjanikov:
Shape Non-rigid Kinematics (SNK): A Zero-Shot Method for Non-Rigid Shape Matching via Unsupervised Functional Map Regularized Reconstruction. NeurIPS 2023 - [i9]Souhaib Attaiki, Maks Ovsjanikov:
NCP: Neural Correspondence Prior for Effective Unsupervised Shape Matching. CoRR abs/2301.05839 (2023) - [i8]Souhaib Attaiki, Lei Li, Maks Ovsjanikov:
Generalizable Local Feature Pre-training for Deformable Shape Analysis. CoRR abs/2303.15104 (2023) - [i7]Souhaib Attaiki, Maks Ovsjanikov:
Understanding and Improving Features Learned in Deep Functional Maps. CoRR abs/2303.16527 (2023) - [i6]Vincent Mallet, Souhaib Attaiki, Maks Ovsjanikov:
AtomSurf : Surface Representation for Learning on Protein Structures. CoRR abs/2309.16519 (2023) - [i5]Sara Hahner, Souhaib Attaiki, Jochen Garcke, Maks Ovsjanikov:
Unsupervised Representation Learning for Diverse Deformable Shape Collections. CoRR abs/2310.18141 (2023) - 2022
- [j1]Nicholas Sharp
, Souhaib Attaiki, Keenan Crane, Maks Ovsjanikov:
DiffusionNet: Discretization Agnostic Learning on Surfaces. ACM Trans. Graph. 41(3): 27:1-27:16 (2022) - [c3]Lei Li, Souhaib Attaiki, Maks Ovsjanikov:
SRFeat: Learning Locally Accurate and Globally Consistent Non-Rigid Shape Correspondence. 3DV 2022: 144-154 - [c2]Souhaib Attaiki, Maks Ovsjanikov:
NCP: Neural Correspondence Prior for Effective Unsupervised Shape Matching. NeurIPS 2022 - [i4]Lei Li, Souhaib Attaiki, Maks Ovsjanikov:
SRFeat: Learning Locally Accurate and Globally Consistent Non-Rigid Shape Correspondence. CoRR abs/2209.07806 (2022) - 2021
- [c1]Souhaib Attaiki, Gautam Pai, Maks Ovsjanikov:
DPFM: Deep Partial Functional Maps. 3DV 2021: 175-185 - [i3]Souhaib Attaiki, Gautam Pai, Maks Ovsjanikov:
DPFM: Deep Partial Functional Maps. CoRR abs/2110.09994 (2021) - [i2]Riccardo Marin, Souhaib Attaiki, Simone Melzi, Emanuele Rodolà, Maks Ovsjanikov:
Why you should learn functional basis. CoRR abs/2112.07289 (2021) - 2020
- [i1]Nicholas Sharp, Souhaib Attaiki, Keenan Crane, Maks Ovsjanikov:
Diffusion is All You Need for Learning on Surfaces. CoRR abs/2012.00888 (2020)
Coauthor Index
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