
Deborah Pintani, Ariel Caputo, Noah Lewis, Marc Stamminger, Fabio Pellacini, Andrea Giachetti
Computer Graphics International Conference 2026 CGI 26 ⭐ Best Presentation
This work introduces a two-stage Gaussian Splatting approach for outdoor scene reconstruction. It separates foreground and background to improve novel-view synthesis and speed up rendering using an environment map.
Deborah Pintani, Ariel Caputo, Noah Lewis, Marc Stamminger, Fabio Pellacini, Andrea Giachetti
Computer Graphics International Conference 2026 CGI 26 ⭐ Best Presentation
This work introduces a two-stage Gaussian Splatting approach for outdoor scene reconstruction. It separates foreground and background to improve novel-view synthesis and speed up rendering using an environment map.

Deborah Pintani, Giulia Benvegnù, Federico Maria Lorusso, Cristiano Chiamulera, Andrea Giachetti, Ariel Caputo
CHItaly 2025 - 16th Biannual Conference of the Italian SIGCHI Chapter CHItaly 25
This work investigates how the visual realism of Virtual Reality environments affects visual attention and presence. It also explores whether head tracking can be used as a simple alternative to eye tracking for measuring visual saliency.
Deborah Pintani, Giulia Benvegnù, Federico Maria Lorusso, Cristiano Chiamulera, Andrea Giachetti, Ariel Caputo
CHItaly 2025 - 16th Biannual Conference of the Italian SIGCHI Chapter CHItaly 25
This work investigates how the visual realism of Virtual Reality environments affects visual attention and presence. It also explores whether head tracking can be used as a simple alternative to eye tracking for measuring visual saliency.

Deborah Pintani, Ariel Caputo, Daniel Mendes, Andrea Giachetti
Behaviour & Information Technology Journal
Extension of the paper CIDER.
Deborah Pintani, Ariel Caputo, Daniel Mendes, Andrea Giachetti
Behaviour & Information Technology Journal
Extension of the paper CIDER.

Deborah Pintani, Marco Emporio, Ariel Caputo, Dong Seon Cheng, Lorenzo Genghini, Nicola Tomasoni, Andrea Giachetti
Virtual Reality Software and Technology Conference 2024 VRST 24
This demo presents a Virtual Reality application integrated with an Industry 4.0/5.0 laboratory digital twin. Users can explore the lab in VR and interact with machines to access data and information.
Deborah Pintani, Marco Emporio, Ariel Caputo, Dong Seon Cheng, Lorenzo Genghini, Nicola Tomasoni, Andrea Giachetti
Virtual Reality Software and Technology Conference 2024 VRST 24
This demo presents a Virtual Reality application integrated with an Industry 4.0/5.0 laboratory digital twin. Users can explore the lab in VR and interact with machines to access data and information.

Marco Emporio, Ariel Caputo, Deborah Pintani, Dong Seon Cheng, Thomas De Marchi, Gianmaria Forte, Franco Fummi, Andrea Giachetti
16th ACM SIGCHI Symposium on Engineering Interactive Computing Systems EICS 24
This work presents a Mixed and Virtual Reality system integrated into an Industry 4.0/5.0 demonstration lab. It allows users to monitor and interact with a digital factory through immersive interfaces and gesture-based controls.
Marco Emporio, Ariel Caputo, Deborah Pintani, Dong Seon Cheng, Thomas De Marchi, Gianmaria Forte, Franco Fummi, Andrea Giachetti
16th ACM SIGCHI Symposium on Engineering Interactive Computing Systems EICS 24
This work presents a Mixed and Virtual Reality system integrated into an Industry 4.0/5.0 demonstration lab. It allows users to monitor and interact with a digital factory through immersive interfaces and gesture-based controls.

Deborah Pintani, Ariel Caputo, Daniel Mendes, Andrea Giachetti
CHItaly 2023 - 15th Biannual Conference of the Italian SIGCHI Chapter CHItaly 23
This work presents a collaborative Mixed Reality system for editing shared 3D scenes. It allows users to work independently and safely combine their changes, improving collaboration during design tasks.
Deborah Pintani, Ariel Caputo, Daniel Mendes, Andrea Giachetti
CHItaly 2023 - 15th Biannual Conference of the Italian SIGCHI Chapter CHItaly 23
This work presents a collaborative Mixed Reality system for editing shared 3D scenes. It allows users to work independently and safely combine their changes, improving collaboration during design tasks.

Marco Emporio, Ariel Caputo, Deborah Pintani, Federico Cunico, Federico Girella, Andrea Avogaro, Marco Cristani, Andrea Giachetti
CHItaly 2023 - 15th Biannual Conference of the Italian SIGCHI Chapter CHItaly 23
This demo shows an online gesture recognition system for XR that can detect and classify both static and dynamic hand gestures. It enables more flexible and expressive interaction design for different applications.
Marco Emporio, Ariel Caputo, Deborah Pintani, Federico Cunico, Federico Girella, Andrea Avogaro, Marco Cristani, Andrea Giachetti
CHItaly 2023 - 15th Biannual Conference of the Italian SIGCHI Chapter CHItaly 23
This demo shows an online gesture recognition system for XR that can detect and classify both static and dynamic hand gestures. It enables more flexible and expressive interaction design for different applications.

Ariel Caputo, Andrea Giachetti, Simone Soso, Deborah Pintani, Andrea D’Eusanio, Stefano Pini, Guido Borghi, Alessandro Simoni, Roberto Vezzani, Rita Cucchiara, Andrea Ranieri, Franca Giannini, Katia Lupinetti, Marina Monti, Mehran Maghoumi, Joseph J. LaViola Jr, Minh-Quan Le, Hai-Dang Nguyen, Minh-Triet Tran
Computer & Graphics Journal
This work presents the SHREC 2021 challenge on online hand gesture recognition from skeleton data. It introduces a new dataset of diverse gestures and compares different methods in a real-world recognition scenario.
Ariel Caputo, Andrea Giachetti, Simone Soso, Deborah Pintani, Andrea D’Eusanio, Stefano Pini, Guido Borghi, Alessandro Simoni, Roberto Vezzani, Rita Cucchiara, Andrea Ranieri, Franca Giannini, Katia Lupinetti, Marina Monti, Mehran Maghoumi, Joseph J. LaViola Jr, Minh-Quan Le, Hai-Dang Nguyen, Minh-Triet Tran
Computer & Graphics Journal
This work presents the SHREC 2021 challenge on online hand gesture recognition from skeleton data. It introduces a new dataset of diverse gestures and compares different methods in a real-world recognition scenario.