Neural Rendering of object-based audio-visual scenes
Lead Research Organisation:
University of Surrey
Department Name: Vision Speech and Signal Proc CVSSP
Abstract
This research will investigate the use of neural rendering methods to render general dynamic scenes from object-based representations with the realism of video. Learnt representations of natural spatial and temporal appearance will be exploited through deep network architectures (GAN, VAE etc.) for real time rendering of scenes. The goal is to enable the reproduction of highly-realistic content for natural scenes from object based scene representations derived from video capture.
Organisations
People |
ORCID iD |
Adrian Hilton (Primary Supervisor) | |
Oliver Camilleri (Student) |
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
EP/R513350/1 | 30/09/2018 | 29/09/2023 | |||
2644080 | Studentship | EP/R513350/1 | 03/01/2022 | 29/06/2025 | Oliver Camilleri |
EP/T518050/1 | 30/09/2020 | 29/09/2025 | |||
2644080 | Studentship | EP/T518050/1 | 03/01/2022 | 29/06/2025 | Oliver Camilleri |