activity
20172021
most citedCombining Deep and Depth: Deep Learning and Face Depth Maps for Driver Attention Monitoring

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

collaborators

10 papers

cs.CV20212 cited

SHREC 2021: Track on Skeleton-based Hand Gesture Recognition in the Wild

Ariel Caputo, Andrea Giachetti, Simone Soso +16

Gesture recognition is a fundamental tool to enable novel interaction paradigms in a variety of application scenarios like Mixed Reality environments, touchless public kiosks, ente…

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.CV20182 cited

Combining Deep and Depth: Deep Learning and Face Depth Maps for Driver Attention Monitoring

Guido Borghi

Recently, deep learning approaches have achieved promising results in various fields of computer vision. In this paper, we investigate the combination of deep learning based method…

cs.CV2018

Learn to See by Events: Color Frame Synthesis from Event and RGB Cameras

Stefano Pini, Guido Borghi, Roberto Vezzani

Event cameras are biologically-inspired sensors that gather the temporal evolution of the scene. They capture pixel-wise brightness variations and output a corresponding stream of…

cs.CV2018

Learning to Generate Facial Depth Maps

Stefano Pini, Filippo Grazioli, Guido Borghi +2

In this paper, an adversarial architecture for facial depth map estimation from monocular intensity images is presented. By following an image-to-image approach, we combine the adv…

cs.CV2017

Head Detection with Depth Images in the Wild

Diego Ballotta, Guido Borghi, Roberto Vezzani +1

Head detection and localization is a demanding task and a key element for many computer vision applications, like video surveillance, Human Computer Interaction and face analysis.…