- Rafał Mantiuk
- Professor of 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
- Room
- SS22
- Phone
- office: +44 1223 763831
- rafal [dot] mantiuk [at] cl [dot] cam [dot] ac [dot] uk
-
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Reserach interest
Applied visual perception; high dynamic range imaging; display algorithms; machine learning for image synthesis; tone-mapping; video coding for new display technologies; image and video quality metrics; 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.
Biography
- Professor/Reader of Graphics and Displays, University of Cambridge, Computer Laboratory, UK (from 2018)
- Senior Lecturer, University of Cambridge, Computer Laboratory, UK (2015-2018)
- 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)
Recent projects
AR-DAVID is a video quality dataset that captures how distortions due to display technologies (e.g, waveguide non-uniformity) are going to be seen on an optical see-through AR display. We found a simple blending of the environment and display light cannot predict the visibility of distortions.
elaTCSF is a temporal contrast sensitivity model that can predict the visibility of a flicker, such as a flicker found in variable-refresh-rate OLED and LCD displays.
ColorVideoVDP is a differentiable image and video quality metric that models human color and spatiotemporal vision. It is targeted and calibrated to assess image distortions due to AR/VR display technologies and video streaming, and it can handle both SDR and HDR content.
See more projects.
Recent papers
- elaTCSF: A Temporal Contrast Sensitivity Function for Flicker Detection and Modeling Variable Refresh Rate Flicker
Yancheng Cai, Ali Bozorgian, Maliha Ashraf, Robert Wanat, and Rafał K. Mantiuk.
In: Proc. of SIGGRAPH Asia 2024, 2024
(doi) (project page) (PDF) (code) - AR-DAVID: Augmented Reality Display Artifact Video Dataset
Alexandre Chapiro, Dongyeon Kim, Yuta Asano, Rafał K. Mantiuk.
In: ACM Transactions on Graphics (Proc. of SIGGRAPH Asia 2024), 43(6), article no. 186, 2024
(project page) (dataset) (PDF) (code) - Color-Accurate Camera Capture with Multispectral Illumination and Multiple Exposures
Hongyun Gao, Rafał K. Mantiuk, Graham D. Finlayson.
In: Computer Graphics Forum (Proc. of Pacific Graphics), 2024
(PDF) - Tracking eye position and gaze direction in near-eye volumetric displays
Marek Wernikowski, Joseph G. March, Radosław Mantiuk, Ali Özgür Yöntem, Rafał K. Mantiuk.
In: Intenational Symposium on Mixed and Augmented Reality, pp. (in print), 2024
(PDF) - Hypernetworks for Generalizable BRDF Representation
Fazilet Gokbudak, Alejandro Sztrajman, Chenliang Zhou, Fangcheng Zhong, Rafal Mantiuk, Cengiz Oztireli.
In: Proc. European Conference on Computer Vision (ECCV), 2024
(doi)
See all papers.
Awards and grants
- HDR-VDP-2 paper received the Test-of-Time Award from SIGGRAPH (2023) for "a significant and lasting impact on computer graphics and interactive techniques over at least a decade"
- HDR-VDP-3 won the 1st place in the HDR Video Quality Measurement Grand Challenge (2023) in the full-reference category
- Color Imaging Conference 2022 (CIC30) Best Paper Award for the paper Suprathreshold contrast matching between different luminance levels
- London Imaging Meeting 2022 Best Paper Award for the paper A Comparative Study on the Loss Functions for Image Enhancement Networks
- ACM SIGGRAPH European Conference on Visual Media Production (CVMP 2022) Best Paper Award for the paper Distilling Style from Image Pairs for Global Forward and Inverse Tone Mapping
- Color Imaging Conference (CIC28) Best Paper Award for the paper Practical color contrast sensitivity functions for luminance levels up to 10000 cd/m2
- Electronic Imaging / Human Vision and Electronic Imaging 2020 Best Paper Award for the paper Predicting visible flicker in temporally changing images
- The IEEE Virtual Reality 2019 Best Journal Paper - for the paper Temporal Resolution Multiplexing: Exploiting the limitations of spatio-temporal vision for more efficient VR rendering
- Electronic Imaging / Human Vision and Electronic Imaging 2019 Best Paper Award for the paper A visual model for predicting chromatic banding artifacts
- ERC Consolidator Grant (2017) - EyeCode: 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.