Imperial College London


Faculty of EngineeringDepartment of Computing

Professor in Machine Learning & Computer Vision



+44 (0)20 7594 8461s.zafeiriou Website CV




375Huxley BuildingSouth Kensington Campus






BibTex format

author = {Cheng, S and Kotsia, I and Pantic, M and Zafeiriou, S},
doi = {10.1109/CVPR.2018.00537},
pages = {5117--5126},
publisher = {IEEE},
title = {4DFAB: A large scale 4D database for facial expression analysis and biometric applications},
url = {},
year = {2018}

RIS format (EndNote, RefMan)

AB - The progress we are currently witnessing in many computer vision applications, including automatic face analysis, would not be made possible without tremendous efforts in collecting and annotating large scale visual databases. To this end, we propose 4DFAB, a new large scale database of dynamic high-resolution 3D faces (over 1,800,000 3D meshes). 4DFAB contains recordings of 180 subjects captured in four different sessions spanning over a five-year period. It contains 4D videos of subjects displaying both spontaneous and posed facial behaviours. The database can be used for both face and facial expression recognition, as well as behavioural biometrics. It can also be used to learn very powerful blendshapes for parametrising facial behaviour. In this paper, we conduct several experiments and demonstrate the usefulness of the database for various applications. The database will be made publicly available for research purposes.
AU - Cheng,S
AU - Kotsia,I
AU - Pantic,M
AU - Zafeiriou,S
DO - 10.1109/CVPR.2018.00537
EP - 5126
PY - 2018///
SN - 1063-6919
SP - 5117
TI - 4DFAB: A large scale 4D database for facial expression analysis and biometric applications
UR -
UR -
UR -
ER -