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2020 – today
- 2023
[b1]Nicolas Donati:
Robust representations for supervised and unsupervised 3D shape matching. (Représentations robustes pour la mise en correspondence de formes 3D via apprentissage supervisé et non-supervisé). Polytechnic Institute of Paris, Palaiseau, France, 2023- 2022
- [j1]Nicolas Donati, Etienne Corman, Simone Melzi, Maks Ovsjanikov:
Complex Functional Maps: A Conformal Link Between Tangent Bundles. Comput. Graph. Forum 41(1): 317-334 (2022) - [c3]Nicolas Donati, Etienne Corman, Maks Ovsjanikov:
Deep orientation-aware functional maps: Tackling symmetry issues in Shape Matching. CVPR 2022: 732-741 - [c2]Lei Li, Nicolas Donati, Maks Ovsjanikov:
Learning Multi-resolution Functional Maps with Spectral Attention for Robust Shape Matching. NeurIPS 2022 - [i4]Nicolas Donati, Etienne Corman, Maks Ovsjanikov:
Deep Orientation-Aware Functional Maps: Tackling Symmetry Issues in Shape Matching. CoRR abs/2204.13453 (2022) - [i3]Lei Li, Nicolas Donati, Maks Ovsjanikov:
Learning Multi-resolution Functional Maps with Spectral Attention for Robust Shape Matching. CoRR abs/2210.06373 (2022) - 2021
- [i2]Nicolas Donati, Etienne Corman, Simone Melzi, Maks Ovsjanikov:
Complex Functional Maps : a Conformal Link Between Tangent Bundles. CoRR abs/2112.09546 (2021) - 2020
- [c1]Nicolas Donati, Abhishek Sharma, Maks Ovsjanikov:
Deep Geometric Functional Maps: Robust Feature Learning for Shape Correspondence. CVPR 2020: 8589-8598 - [i1]Nicolas Donati, Abhishek Sharma, Maks Ovsjanikov:
Deep Geometric Functional Maps: Robust Feature Learning for Shape Correspondence. CoRR abs/2003.14286 (2020)
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