University of Oulu

Kollias D., Cheng S., Pantic M., Zafeiriou S. (2019) Photorealistic Facial Synthesis in the Dimensional Affect Space. In: Leal-Taixé L., Roth S. (eds) Computer Vision – ECCV 2018 Workshops. ECCV 2018. Lecture Notes in Computer Science, vol 11130. Springer, Cham,

Photorealistic facial synthesis in the dimensional affect space

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Author: Kollias, Dimitrios1; Cheng, Shiyang1; Pantic, Maja1;
Organizations: 1Department of Computing, Imperial College London, London, UK
2Centre for Machine Vision and Signal Analysis, University of Oulu, Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 6.4 MB)
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Language: English
Published: Springer Nature, 2019
Publish Date: 2019-10-03


This paper presents a novel approach for synthesizing facial affect, which is based on our annotating 600,000 frames of the 4DFAB database in terms of valence and arousal. The input of this approach is a pair of these emotional state descriptors and a neutral 2D image of a person to whom the corresponding affect will be synthesized. Given this target pair, a set of 3D facial meshes is selected, which is used to build a blendshape model and generate the new facial affect. To synthesize the affect on the 2D neutral image, 3DMM fitting is performed and the reconstructed face is deformed to generate the target facial expressions. Last, the new face is rendered into the original image. Both qualitative and quantitative experimental studies illustrate the generation of realistic images, when the neutral image is sampled from a variety of well known databases, such as the Aff-Wild, AFEW, Multi-PIE, AFEW-VA, BU-3DFE, Bosphorus.

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Series: Lecture notes in computer science
ISSN: 0302-9743
ISSN-E: 1611-3349
ISSN-L: 0302-9743
ISBN: 978-3-030-11012-3
ISBN Print: 978-3-030-11011-6
Volume: 11130
Pages: 475 - 491
DOI: 10.1007/978-3-030-11012-3_36
Host publication: Computer Vision – ECCV 2018 Workshops. ECCV 2018, Munich, Germany, September 8-14, 2018, Proceedings, Part II
Host publication editor: Leal-Taixé, Laura
Roth, Stefan
Conference: European conference on computer vision
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
213 Electronic, automation and communications engineering, electronics
Funding: The work of Dimitris Kollias was funded by a Teaching Fellowship of Imperial College London. The work of S. Cheng is funded by the EPSRC project EP/J017787/1 (4D-FAB) and EP/N007743/1 (FACER2VM).
Copyright information: © Springer Nature Switzerland AG 2019. This is a post-peer-review, pre-copyedit version of an article published in Lecture Notes in Computer Science. The final authenticated version is available online at: