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Deep Face Generation

The creation and animation of digital characters in movies, TV productions and social interactions requires detailed 3D models of their facial morphologies. Typically, for digital doubles of real actors these models are obtained from 3D captures of the actor face using complex hardware setups or a high number of hours of manual work by artists.
The purpose of this internship is to investigate an alternative, where the facial appearance would be generated using a deep generative network (GAN) and some constraints to drive the result.
A first objective will be to evaluate performances and limitations of existing solutions (typically styleGAN2 and FTGAN). Then evaluate how to ingest “features” to drive the generation of faces (also called text to face generation). And finally develop a solution to map the generated “appearance” on a proprietary 3D adapted face model.

http://arxiv.org/abs/1912.04958
https://arxiv.org/abs/1904.05729

The internship is located at InterDigital Research & Innovation, Rennes, France


Mots-clés
generative adversarial networks, deep learning, 3D modelling, facial appearance, face models, CGI
Établissement
InterDigital R&D
35576 Cesson-Sevigne   
Site Web
https://research-ri.interdigital.com/
Langues obligatoires
Anglais; Français
Niveau
Bac +4; Bac +5
Prérequis

Deep learning theory and frameworks, Python.

Durée
4 to 6 months
Date limite
01/09/2020
Informations de contact

Philippe GUILLOTEL, philippe.guillotel@interdigital.com