2 citations · 2 across the 3 of their papers we have counts for
7 papers
Reduced Representation of Deformation Fields for Effective Non-rigid Shape Matching
Ramana Sundararaman, Riccardo Marin, Emanuele Rodola +1
In this work we present a novel approach for computing correspondences between non-rigid objects, by exploiting a reduced representation of deformation fields. Different from exist…
A functional skeleton transfer
Pietro Musoni, Riccardo Marin, Simone Melzi +1
The animation community has spent significant effort trying to ease rigging procedures. This is necessitated because the increasing availability of 3D data makes manual rigging inf…
Shape registration in the time of transformers
Giovanni Trappolini, Luca Cosmo, Luca Moschella +3
In this paper, we propose a transformer-based procedure for the efficient registration of non-rigid 3D point clouds. The proposed approach is data-driven and adopts for the first t…
Correspondence Learning via Linearly-invariant Embedding
Riccardo Marin, Marie-Julie Rakotosaona, Simone Melzi +1
In this paper, we propose a fully differentiable pipeline for estimating accurate dense correspondences between 3D point clouds. The proposed pipeline is an extension and a general…
High-Resolution Augmentation for Automatic Template-Based Matching of Human Models
Riccardo Marin, Simone Melzi, Emanuele Rodolà +1
We propose a new approach for 3D shape matching of deformable human shapes. Our approach is based on the joint adoption of three different tools: an intrinsic spectral matching pip…
Instant recovery of shape from spectrum via latent space connections
Riccardo Marin, Arianna Rampini, Umberto Castellani +3
We introduce the first learning-based method for recovering shapes from Laplacian spectra. Given an auto-encoder, our model takes the form of a cycle-consistent module to map laten…