activity
20172021
most citedInfinite Feature Selection: A Graph-based Feature Filtering Approach

244 citations · 244 across the 3 of their papers we have counts for

collaborators

8 papers

cs.GR2021

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…

cs.CV2021

Localized Shape Modelling with Global Coherence: An Inverse Spectral Approach

Marco Pegoraro, Simone Melzi, Umberto Castellani +2

Many natural shapes have most of their characterizing features concentrated over a few regions in space. For example, humans and animals have distinctive head shapes, while inorgan…

cs.CV2020

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…

cs.CV2020★ 244 cited

Infinite Feature Selection: A Graph-based Feature Filtering Approach

Giorgio Roffo, Simone Melzi, Umberto Castellani +2

We propose a filtering feature selection framework that considers subsets of features as paths in a graph, where a node is a feature and an edge indicates pairwise (customizable) r…

cs.CV2020

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…

cs.CV2018

FARM: Functional Automatic Registration Method for 3D Human Bodies

Riccardo Marin, Simone Melzi, Emanuele Rodolà +1

We introduce a new method for non-rigid registration of 3D human shapes. Our proposed pipeline builds upon a given parametric model of the human, and makes use of the functional ma…

cs.CV2017

Infinite Latent Feature Selection: A Probabilistic Latent Graph-Based Ranking Approach

Giorgio Roffo, Simone Melzi, Umberto Castellani +1

Feature selection is playing an increasingly significant role with respect to many computer vision applications spanning from object recognition to visual object tracking. However,…

cs.GR2017

Localized Manifold Harmonics for Spectral Shape Analysis

Simone Melzi, Emanuele Rodolà, Umberto Castellani +1

The use of Laplacian eigenfunctions is ubiquitous in a wide range of computer graphics and geometry processing applications. In particular, Laplacian eigenbases allow generalizing…