PhD Studentship: A Facial Inpainting Framework for Virtual Try-on Technology

Manchester Metropolitan University

Summary

This is a joint PhD studentship between Manchester Metropolitan and Image Metrics Ltd, funded by The Royal Society. This project will improve the realism of facial appearance try-on technology by developing a novel and light-weight solution for real-time inpainting. This research will investigate deep learning architectures for various inpainting tasks.

Aims and objectives

Virtual try-on technology assists consumer in making purchase decision when shop online. With the popularity of mobile devices, virtual try-on for faces has been widely used for cosmetic and gaming. In medical practices for face reconstruction surgery, there is a growing need to be able to find the realistic appearance for people with face defects. In addition, the ability to predict a face with occlusion can improve the face recognition rate in security application. This project proposes a new technique that can inpaint the missing face region with realistic appearance. Recent work shows the ability to inpaint face regions however these methods only work on small images and take a long processing time. This project will design a solution using a machine intelligence method that work efficiently on mobile devices. The solution will be tested and deployed in collaboration with Image Metrics Ltd in real-world applications.

The PhD candidate will receive professional development training from the University, the industry partner and attend external training. To ensure the candidate has exposure to commercial setting, s/he will spend 60% of their time at Manchester Metropolitan University and 40% at Image Metrics Ltd (http://image-metrics.com). The joint supervision will broaden the perspective on the research impact and enrich the student experience as s/he gains a wider understanding of applied research and different training environments. The PhD student will have access to training, facilities and expertise in both organisations, which is very valuable particularly in enhancing their employability, ideally becoming a leader in her/his field. With such setting, the student will benefit from different algorithm/software development with an applied or translational dimension.

Specific requirements of the project

Candidates must have a strong motivation for research and excellent programming skills. Expertise of developing computer vision and machine learning algorithms would be desirable, with an interest in face analysis.

Qualifications:

  • A high grade undergraduate degree (first class or upper second) in Computer Science
  • A MSc level in Computer Science would be desirable for this post
  • Knowledge of software development and programming, including C/C++/Java, OpenCV and Matlab
  • Experience of designing experiments and running statistical analyses, in Matlab, R, or SPSS
  • Good communication and writing skills
  • Developing image analysis/machine learning algorithms would be beneficial
  • Able to work as part of a joint academia and industry team

Home/EU fees will be covered and a stipend of £14,777 per annum. The candidate will also receive training on image processing techniques and software development, alongside aspects of face detection and recognition.

This opportunity is open to Home/EU and International applicants. Please note, International applicants must cover the difference in fees.

Informal enquiries to:

Moi Hoon Yap m.yap@mmu.ac.uk

Interviews June

Start July

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Advert information

Type / Role:

PhD

Location(s):

Northern England