Photorealistic facial synthesis in the dimensional affect space

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Title: Photorealistic facial synthesis in the dimensional affect space
Authors: Kollias, D
Cheng, S
Pantic, M
Zafeiriou, S
Item Type: Conference Paper
Abstract: 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.
Issue Date: 29-Jan-2019
Date of Acceptance: 8-Sep-2018
ISBN: 9783030110116
ISSN: 0302-9743
Publisher: Springer
Start Page: 475
End Page: 491
Journal / Book Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume: 11130 LNCS
Copyright Statement: © 2019, Springer Nature Switzerland AG.
Sponsor/Funder: Engineering & Physical Science Research Council (EPSRC)
Engineering & Physical Science Research Council (E
Funder's Grant Number: EP/J017787/1
Conference Name: European Conference on Computer Vision
Keywords: 08 Information and Computing Sciences
Artificial Intelligence & Image Processing
Publication Status: Published
Start Date: 2018-09-08
Finish Date: 2018-09-14
Conference Place: Munich, Germany
Embargo Date: 2020-01-29
Online Publication Date: 2019-01-29
Appears in Collections:Computing

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