2 citations · 3 across the 5 of their papers we have counts for
10 papers
Multi-Category Mesh Reconstruction From Image Collections
Alessandro Simoni, Stefano Pini, Roberto Vezzani +1
Recently, learning frameworks have shown the capability of inferring the accurate shape, pose, and texture of an object from a single RGB image. However, current methods are traine…
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…
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…
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…
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…
Learning to Detect and Track Visible and Occluded Body Joints in a Virtual World
Matteo Fabbri, Fabio Lanzi, Simone Calderara +3
Multi-People Tracking in an open-world setting requires a special effort in precise detection. Moreover, temporal continuity in the detection phase gains more importance when scene…