14 citations · 14 across the 1 of their papers we have counts for
3 papers
cs.CV2022★ 14 cited
Learning Multi-resolution Functional Maps with Spectral Attention for Robust Shape Matching
Lei Li, Nicolas Donati, Maks Ovsjanikov
In this work, we present a novel non-rigid shape matching framework based on multi-resolution functional maps with spectral attention. Existing functional map learning methods all…
cs.CV2022
Deep Orientation-Aware Functional Maps: Tackling Symmetry Issues in Shape Matching
Nicolas Donati, Etienne Corman, Maks Ovsjanikov
State-of-the-art fully intrinsic networks for non-rigid shape matching often struggle to disambiguate the symmetries of the shapes leading to unstable correspondence predictions. M…
stat.ML2020
Deep Geometric Functional Maps: Robust Feature Learning for Shape Correspondence
Nicolas Donati, Abhishek Sharma, Maks Ovsjanikov
We present a novel learning-based approach for computing correspondences between non-rigid 3D shapes. Unlike previous methods that either require extensive training data or operate…