most citedClassifying Signals on Irregular Domains via Convolutional Cluster Pooling

6 citations · 8 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG20191 cited

A Deep Learning based approach to VM behavior identification in cloud systems

Matteo Stefanini, Riccardo Lancellotti, Lorenzo Baraldi +1

Cloud computing data centers are growing in size and complexity to the point where monitoring and management of the infrastructure become a challenge due to scalability issues. A p…

cs.CV20191 cited

Multi-views Embedding for Cattle Re-identification

Luca Bergamini, Angelo Porrello, Andrea Capobianco Dondona +4

People re-identification task has seen enormous improvements in the latest years, mainly due to the development of better image features extraction from deep Convolutional Neural N…

cs.LG20196 cited

Classifying Signals on Irregular Domains via Convolutional Cluster Pooling

Angelo Porrello, Davide Abati, Simone Calderara +1

We present a novel and hierarchical approach for supervised classification of signals spanning over a fixed graph, reflecting shared properties of the dataset. To this end, we intr…

cs.CV2019

Domain Translation with Conditional GANs: from Depth to RGB Face-to-Face

Matteo Fabbri, Guido Borghi, Fabio Lanzi +3

Can faces acquired by low-cost depth sensors be useful to catch some characteristic details of the face? Typically the answer is no. However, new deep architectures can generate RG…

cs.CV2019

Can Adversarial Networks Hallucinate Occluded People With a Plausible Aspect?

Federico Fulgeri, Matteo Fabbri, Stefano Alletto +2

When you see a person in a crowd, occluded by other persons, you miss visual information that can be used to recognize, re-identify or simply classify him or her. You can imagine i…