Hello!
I am Federico, a PhD student at EPFL in Lausanne, Switzerland. I work on 3D Computer Vision in EPFL’s CVLab, supervised by Prof. Pascal Fua. My research lies mainly on neural implicit representations for 3D surfaces, with a particular interest in surfaces with difficult topologies, represented using Unsigned Distance Fields. Neural representations are quite fun in general, so I'm also working on image compression using them.
A part from research, I love beach tennis (as clear from the pic on the right), bouldering, photography, and I play a bit of music (guitar, drums, sing). If you want to see my research, it's below; if you want to see my pics and music, here's my YouTube and Instagram :)Publications
(full list on scholar)
Neural Surface Detection for Unsigned Distance Fields
Federico Stella, Nicolas Talabot, Hieu Le, Pascal Fua; at ECCV 2024
A neural approach to turn a UDF into a local SDF, which can be meshed with traditional algorithms.
MeshUDF: Fast and Differentiable Meshing of Unsigned Distance Field Networks
Benoit Guillard, Federico Stella, Pascal Fua; at ECCV 2022
An extension of Marching Cubes to mesh non-watertight surfaces, applied the output of Unsigned Distance Field networks. We also derive gradients for the reconstructed vertex positions wrt. the UDF field.
Compass: Learning to Orient Surfaces by Self-supervised Spherical CNNs
Riccardo Spezialetti, Federico Stella, Marlon Marcon, Luciano Silva, Samuele Salti, Luigi Di Stefano; at NeurIPS 2020
The first end-to-end trained Local Reference Frame for point clouds. It employs Spherical CNNs to extract rotation-invariant features from point clouds, and uses them to locally orient surface patches in a canonical way.