Fabio Ganovelli

Dr. Fabio Ganovelli

Visual Computing Laboratory, ISTI-CNR, Pisa, Italy

Research Focus & Metrics

Academic Career Length

22Years (2005-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
31 August 2005 in The Visual Computer
Verified
Journal Article
Closed access
PDF file
TFThomas Franken
Thomas Franken
MDMatteo Dellepiane
Matteo Dellepiane
Fabio GanovelliFabio Ganovelli
Fabio Ganovelli
Paolo CignoniPaolo Cignoni
Paolo Cignoni
CMClaudio Montani
Claudio Montani
Roberto ScopignoRoberto Scopigno
Roberto Scopigno

18 March 2008 in The Visual Computer
Verified
Journal Article
Closed access
PDF file
NPNico Pietroni
Nico Pietroni
Fabio GanovelliFabio Ganovelli
Fabio Ganovelli
Paolo CignoniPaolo Cignoni
Paolo Cignoni
Roberto ScopignoRoberto Scopigno
Roberto Scopigno

1 September 2019 in Signal Processing: Image Communication
Verified
Journal Article
Closed access
Nicola CapeceNicola Capece
Nicola Capece
Francesco BanterleFrancesco Banterle
Francesco Banterle
Paolo CignoniPaolo Cignoni
Paolo Cignoni
Fabio GanovelliFabio Ganovelli
Fabio Ganovelli
Roberto ScopignoRoberto Scopigno
Roberto Scopigno
Ugo ErraUgo Erra
Ugo Erra

31 July 2015 in The Visual Computer
Verified
Journal Article
Closed access
PDF file
ABAndrea Baldacci
Andrea Baldacci
DBDaniele Bernabei
Daniele Bernabei
Massimiliano CorsiniMassimiliano Corsini
Massimiliano Corsini
Fabio GanovelliFabio Ganovelli
Fabio Ganovelli
Roberto ScopignoRoberto Scopigno
Roberto Scopigno

1 January 2020 in IEEE Computer Graphics and Applications
Verified
Journal Article
Closed access
Nicola CapeceNicola Capece
Nicola Capece
Francesco BanterleFrancesco Banterle
Francesco Banterle
Paolo CignoniPaolo Cignoni
Paolo Cignoni
Fabio GanovelliFabio Ganovelli
Fabio Ganovelli
Ugo ErraUgo Erra
Ugo Erra
We introduce a novel algorithm that turns a flash selfie taken with a smartphone into a studio-like photograph with uniform lighting. Our method uses a convolutional neural network trained on a set of pairs of photographs acquired in a controlled environment. For each pair, we have one photograph of a subject's face taken with the camera flash enabled and another one of the same subject in the same pose illuminated using a photographic studio-lighting setup. We show how our method can amend lighting artifacts introduced by a close-up camera flash, such as specular highlights, shadows, and skin shine.

1 January 2008
Verified
Conference Paper
Open access
Paolo CignoniPaolo Cignoni
Paolo Cignoni
Fabio GanovelliFabio Ganovelli
Fabio Ganovelli
EGEnrico Gobbetti
Enrico Gobbetti
FMFabio Marton
Fabio Marton
FPFederico Ponchio
Federico Ponchio
RSRoberto Scopigno
Roberto Scopigno