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  Implicit neural representations for facial animation


   Department of Computer Science

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  Dr Vinay Namboodiri  No more applications being accepted  Competition Funded PhD Project (UK Students Only)

About the Project

The University of Bath is inviting applications for the following PhD project commencing in October 2023 under the supervision of Dr Vinay Namboodiri in the Department of Computer Science.

Overview of the Research:

Facial animation is used widely in gaming and entertainment applications. Traditionally these have been based on explicit mesh-based rigged representations created by artists using motion-capture or scans. Recently, ways for obtaining high-quality synthesis using implicit neural representations such as neural radiance fields (Nerfs) have become possible. There are challenges in obtaining neural representations that can be animated by artists, are generalizable and work well with audio representations. In this project, we intend to investigate methods that could resolve some of these challenges. The techniques involved would include neural rendering, multi-modal neural representations and meta-learning.   

Project keywords: neural rendering, image synthesis, computer vision, computer graphics. 

Candidate Requirements:

Applicants should hold, or expect to receive, a First Class or good Upper Second Class UK Honours degree (or the equivalent) in a relevant subject. A master’s level qualification would also be advantageous.

In addition, applicants should have expertise in python programming, a strong mathematical background and a good general programming proficiency.

Non-UK applicants must meet our English language entry requirement.

Enquiries and Applications:

Informal enquiries are encouraged and should be directed to the lead supervisor, Dr Vinay Namboodiri, on email address [Email Address Removed].

Formal applications should be submitted via the University of Bath’s online application form for a PhD in Computer Science.

More information about applying for a PhD at Bath may be found on our website.

Note: Applications may close earlier than the advertised deadline if a suitable candidate is found. We therefore recommend that you contact the lead supervisor prior to applying and submit your formal application as early as possible.

Funding Eligibility:

To be eligible for funding, you must qualify as a Home student. The eligibility criteria for Home fee status are detailed and too complex to be summarised here in full; however, as a general guide, the following applicants will normally qualify subject to meeting residency requirements: UK and Irish nationals (living in the UK or EEA/Switzerland), those with Indefinite Leave to Remain and EU nationals with pre-settled or settled status in the UK under the EU Settlement Scheme. This is not intended to be an exhaustive list. Additional information may be found on our fee status guidance webpage, on the GOV.UK website and on the UKCISA website

Equality, Diversity and Inclusion:

We value a diverse research environment and aim to be an inclusive university, where difference is celebrated and respected. We welcome and encourage applications from under-represented groups.

If you have circumstances that you feel we should be aware of that have affected your educational attainment, then please feel free to tell us about it in your application form. The best way to do this is a short paragraph at the end of your personal statement.


Computer Science (8)

Funding Notes

The successful candidate will be offered a 4-year Graduate Research Scholarship covering Home tuition fees and providing a stipend (£17,668 per annum, 2022/23 rate) as well as research/training expenses (£1,000 per annum). There is requirement to undertake certain teaching duties in the role of a Teaching Assistant, in addition to working towards a PhD qualification. This activity forms part of the scholarship award and includes tasks such as: teaching tutorials, marking, providing feedback, answering questions and facilitating seminars. Eligibility criteria apply - see Funding Eligibility section above. For more information about the teaching requirement, please contact the lead supervisor.

References

Advances in Neural Rendering
Ayush Tewari, Justus Thies, Ben Mildenhall, Pratul Srinivasan, Edgar Tretschk, Yifan Wang, Christoph Lassner, Vincent Sitzmann, Ricardo Martin-Brualla, Stephen Lombardi, Tomas Simon, Christian Theobalt, Matthias Niessner, Jonathan T. Barron, Gordon Wetzstein, Michael Zollhoefer, Vladislav Golyanik
State of the art report – Eurographics 2022, https://arxiv.org/abs/2111.05849

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