FACER2VM is a five-year research programme aimed at making face recognition ubiquitous by 2021.

The project has develop unconstrained face recognition technology for a broad spectrum of applications. The adopted approach has delivered novel machine learning solutions, which combine the technique of deep learning with sophisticated prior information conveyed by 3D face models.


The goal of the programme was to advance the science of machine face perception and to deliver step change in face matching technology to enable automatic retrieval, recognition, verification and management of faces in images and video.

This was achieved by addressing the challenging problem posed by face appearance variations introduced by a range of natural and image degradation phenomena such as change of viewpoint, illumination, expression, resolution, blur and occlusion, by bringing together leading experts and their research teams at the University of Surrey, Imperial College London, and the University of Stirling.


The financial support from EPSRC Programme Grant “FACER2VM”, reference EP/N007743/1 was gratefully acknowledged.