- Rafał Mantiuk
- Reader in Graphics and Displays
- Department of Computer Science and Technology
- The Computer Laboratory
- Rainbow Research Group
- University of Cambridge
- Office address
- University of Cambridge
- Computer Laboratory
- William Gates Building
- 15 JJ Thomson Avenue
- Cambridge CB3 0FD
- United Kingdom
- office: +44 1223 763831
- rafal [dot] mantiuk [at] cl [dot] cam [dot] ac [dot] uk
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Applied visual perception; high dynamic range imaging; display algorithms; tone-mapping; video coding for new display technologies; image and video quality metric; visibility metrics; virtual reality and low-level perception; computational photography; computational displays; novel display technologies; colour; perception in computer graphics; novel image and video representations (beyond 2D); psychophysics; modeling visual perception with machine learning.
- Senior Lecturer, University of Cambridge, Computer Laboratory, UK (from 2015)
- Lecturer / Senior Lecturer, Bangor University, School of Computer Science, UK (2009-2015)
- Postdoc Fellow, University of British Columbia, Canada (2008-2009)
- Postdoc, Max-Planck-Institut for Computer Science, Germany (2007-2008)
- Internship, Sharp Laboratories of America, Camas WA, USA (2006)
- PhD (summa cum laude, Computer Science), Max-Planck-Institut for Computer Science, Germany (2006)
- Msc (Computer Science), Technical University of Szczecin, Poland (2003)
Every second frame of a high-frame animation is rendered at a lower resolution, reducing the number of rendered and transmitted pixels by about 40%. The high quality animation is reconstructed by exploiting the limitations of human spatio-temporal vision.
Visibility of artifacts is marked by a number of observers to create a dataset of local differences. The dataset is then used to retrain existing visibility metrics, such as HDR-VDP-2, and to train a new CNN-based metric.
The largest image quality dataset, TID2013, is rescaled to improve the quality scores. Better quality estimates are obtained using a more rigorous observer model (Thurstone's Case V) and with additional cross-content and with-reference measurements.
See more projects.
- Temporal Resolution Multiplexing: Exploiting the limitations of spatio-temporal vision for more efficient VR rendering
Gyorgy Denes, Kuba Maruszczyk, George Ash, Rafał K. Mantiuk.
In: IEEE Transactions on Visualization and Computer Graphics, (conditionally accepted), 2019
- A visual model for predicting chromatic banding artifacts
Gyorgy Denes, George Ash, Rafał K. Mantiuk.
In: Human Vision and Electronic Imaging, (to appear 01/2019), 2019
- Hybrid-MST: A Hybrid Active Sampling Strategy for Pairwise Preference Aggregation
Jing Li, Rafał K. Mantiuk and Junle Wang.
In: Proc. of Neural Information Processing Systems (NIPS), 2018
- Naturally glossy: Gloss perception, illumination statistics, and tone mapping
Wendy J. Adams, Gizem Kucukoglu, Michael S. Landy, Rafał K. Mantiuk.
In: Journal of Vision, 18, article no. 4, 2018
- Improving Quality of Anti-Aliasing in Virtual Reality
Kuba Maruszczyk, Gyorgy Denes, Rafał K. Mantiuk.
In: The Computer Graphics & Visual Computing Congerence, Posters, (best poster award), 2018
See all papers.
Awards and grants
- ERC Consolidator Grant (2017) - Perceptual encoding of high fidelity light fields
- MSCA Innovative Training Network (2018) - RealVision: Hyper-realistic Visual Experience
- EPSRC research grant (2017) - A spatio-chromatic colour appearance model for retargeting high-dynamic-range image appearance across viewing conditions
- HPC Wales Research and Innovation grant (2013/14) - Video retargeting for delivery to mobile and future display technologies
- Royal Society Research Grant (2013) - Limiting factors of perceptual image fidelity
- EPSRC grant EP/I006575/1 (2011) - Quantifying image quality in computer graphics
- Heinz Billing Award 2006
My contribution to the organization of research networks and conferences can be found here.