[visionlist] Jobs: PhD position on Deep View Synthesis for VR Video at University of Bath

[Christian Richardt]

*Deep View Synthesis for Virtual Reality Video*

To feel truly immersed in virtual reality, one needs to be able to freely
look around within a virtual environment and see it from the viewpoints of
one’s own eyes. Full immersion requires that viewers see the correct views
of an environment at all times. As viewers move their heads, the objects
they see should move relative to each other, with different speeds
depending on their distance to the viewer. This is called motion parallax
and is a vital depth cue for the human visual system that is entirely
missing from existing 360° VR video.

The goal of this project is to capture the real world and recreate its
appearance for new, previously unseen views, to enable more immersive
virtual reality video experiences. To do this, the project aims to develop
novel-view synthesis techniques using deep learning (like Flynn et al.,
2019) that are capable of producing high-quality, temporally-coherent,
time-varying VR video of dynamic real-world environments from one or more
standard or 360-degree video cameras. Particularly important are the
convincing reconstruction of visual dynamics, such as moving people, cars
and trees. This experience will provide improved motion parallax and depth
perception to the viewer (like Bertel et al., 2019) to ensure unparalleled
realism and immersion.

*Anticipated start date*
28 September 2020

*Candidate*
Candidates should normally have a very good undergraduate degree
(equivalent to First Class), or a Master’s degree in visual computing,
computer science, or a related discipline. A strong mathematical background
and strong previous programming experience, preferably in C++ and/or
Python, is required. Candidates must have a strong interest in visual
computing, and previous experience in computer vision, computer graphics,
deep learning and image processing is highly desirable. Non-UK applicants
must meet our English language entry requirement:
http://www.bath.ac.uk/study/pg/apply/english-language/.

*More Information*
For more general information on studying for a PhD in Computer Science at
Bath, see:
http://www.bath.ac.uk/science/graduate-school/research-programmes/phd-computer-science/

More information about applying for a PhD at Bath may be found here:
http://www.bath.ac.uk/guides/how-to-apply-for-doctoral-study/

Informal enquiries are welcome and should be directed to Dr Christian
Richardt (c.richardt at bath.ac.uk).

*Application*
Formal applications should be made via the University of Bath’s online
application form:
https://samis.bath.ac.uk/urd/sits.urd/run/siw_ipp_lgn.login?process=siw_ipp_app&code1=RDUCM-FP01&code2=0014

Please ensure that you quote the supervisor’s name and project title in the
‘Your research interests’ section.

*Funding Notes*
UK and EU candidates applying for this project will be considered for a
University Research Studentship which will cover UK/EU tuition fees, a
training support fee of £1,000 per annum and a tax-free maintenance
allowance at the UKRI Doctoral Stipend rate (£15,009 in 2019-20) for a
period of up to 3.5 years.

*Note:* *ONLY UK and EU applicants are eligible for this studentship. All
other applicants are NOT eligible for funding.*

*References*
Bertel, Campbell and Richardt, “MegaParallax: Casual 360° Panoramas with
Motion Parallax”, IEEE Transactions on Visualization and Computer Graphics
2019

Flynn, Broxton, Debevec, DuVall, Fyffe, Overbeck, Snavely and Tucker,
“DeepView: View Synthesis With Learned Gradient Descent”. CVPR 2019


Dr Christian Richardt <https://richardt.name/>
*Department of Computer Science, University of Bath*
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