2018-2019
IMRA. Project co-financed by IMRA-Europe
The project aims to develop computer vision solutions based on supervised machine learning that support behavior analysis and prediction of actions and scene evolution for the purpose of autonomous driving.
eSERVANT. Project co-financed under Tuscany POR FESR 2014-2020. Analysing, monitoring and connecting people in large facilities. The eSERVANT project was led by QUID Informatica S.p.A and was carried out in collaboration with the partners Sokom srl, Sintra Consulting srl, Magenta S.R.L. and the DIISM of the University of Siena.
2016-2019
funded by: Leonardo – Finmeccanica
FREEWAY is a technology transfer project in collaboration with the Italian multinational aerospace, defense and security company Finmeccanica. In this project MICC is transferring its know-how in state-of-the-art computer vision for face and full-body recognition and re-identification.
2018-2019
In this project we perform compression artifact removal by learning an image transformation task with a deep residual convolutional neural network. We show that conditional Generative Adversarial Networks produce higher quality images with sharp details which are relevant not only to the human eye but also for semantic computer vision tasks. We propose a GAN ensemble driven by a quality prediction network able to restore images compressed at any rate.