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Makeup face synthesis and verification (CO/HF-Un1/2020)

Project Description

Face makeup is so common in our life and most of women wear makeup once they are presented themselves in public. Although the current state-of-the-art facial recognition systems can recognise faces to some extent under the context, face makeup has become a potential issue to influence the modern AI based systems.

In this project, we will investigate how to use deep learning methods to improve the AI based facial recognition systems so that they become more reliable to the makeup faces by using synthesis technologies and identifying important facial regions under makeup.

Start date: April 2020.

Entry requirements:

• In-depth knowledge of fundamentals and state-of-the-art in machine learning or a related field.
• Experience with deep neural networks and machine learning
• Self-motivated and excellent problem-solving skills
• Solid programming skills with Python and proficient with Unix/Linux.
• Experience with ML toolkits, e.g. TensorFlow, PyTorch, etc.
• Preferable: a Master with equivalent experience in the areas of machine learning or a related field (industrial experience is beneficial).

How to apply:

All applications are made online, please select the school/department name under the programme name section and include the quote reference number.

Funding Notes

This is an open call for candidates who are sponsored or who have their own funding. If you do not have funding, you may still apply, however Institutional funding is not guaranteed. Outstanding candidates (UK/EU/International) without funding will be considered for funding opportunities which may become available in the School.

Band RB (UK/EU: TBC; international: £22,350).

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