Explore the words cloud of the RealVision project. It provides you a very rough idea of what is the project "RealVision" about.
The following table provides information about the project.
DANMARKS TEKNISKE UNIVERSITET
|Coordinator Country||Denmark [DK]|
|Total cost||4˙076˙702 €|
|EC max contribution||4˙076˙702 € (100%)|
1. H2020-EU.1.3.1. (Fostering new skills by means of excellent initial training of researchers)
|Duration (year-month-day)||from 2018-01-01 to 2021-12-31|
Take a look of project's partnership.
|1||DANMARKS TEKNISKE UNIVERSITET||DK (KGS LYNGBY)||coordinator||580˙163.00|
|2||THE CHANCELLOR MASTERS AND SCHOLARSOF THE UNIVERSITY OF CAMBRIDGE||UK (CAMBRIDGE)||participant||819˙863.00|
|3||UNIVERSITE DE NANTES||FR (NANTES CEDEX 1)||participant||525˙751.00|
|4||BANG & OLUFSEN AS||DK (STRUER)||participant||290˙081.00|
|5||FORCE TECHNOLOGY||DK (BRONDBY)||participant||290˙081.00|
|6||BANGOR UNIVERSITY||UK (BANGOR)||participant||273˙287.00|
|7||THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD||UK (OXFORD)||participant||273˙287.00|
|8||CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS||FR (PARIS)||participant||262˙875.00|
|9||DXO LABS||FR (BOULOGNE BILLANCOURT)||participant||262˙875.00|
|10||FRAUNHOFER GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG E.V.||DE (MUNCHEN)||participant||249˙216.00|
|11||MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV||DE (MUENCHEN)||participant||249˙216.00|
|13||BARCO NV||BE (KORTRIJK)||partner||0.00|
|14||BRITISH BROADCASTING CORPORATION||UK (LONDON)||partner||0.00|
|15||MCMASTER UNIVERSITY||CA (HAMILTON)||partner||0.00|
|16||Phase One||DK (Frederiksberg)||partner||0.00|
|17||Spectral Edge||UK (Cambridge)||partner||0.00|
|18||ST Microelectronics||FR (Grenoble)||partner||0.00|
|19||Stanford University||US (STANFORD)||partner||0.00|
|20||Technicolor R&D France||FR (ISSY LES MOULINEAUX)||partner||0.00|
|21||University of California, Berkeley||US (Berkeley, CA)||partner||0.00|
The aim of realistic digital imaging is the creation of high quality imagery, which faithfully represents the physical environment. The ultimate goal is to create images, which are perceptually indistinguishable from a real scene. The RealVision network brings together leading universities, centers focused on industrial development and companies in Multimedia, Optics, Visual Communication, Visual Computing, Computer Graphics and Human Vision research across Europe, with the aim of training a new generation of scientists, technologists, and entrepreneurs that will move Europe into a leading role in innovative hyper-realistic imaging technologies. Current imaging technologies capture only a fraction of visual information that the human eye can see. The colours and dynamic range are inadequate for most real-world scenes and not all depth cues required for natural 3D vision are captured. This limits the realism of the experience and has hampered the introduction of 3D technology. Advancement in imaging technologies makes it possible to circumvent these bottlenecks in visual systems. As a result, new visual signal-processing areas have emerged such as light fields, ultra-high definition, highframe rate and high dynamic range imaging. The novel combinations of those technologies can facilitate a hyper-realistic visual experience. This will without doubt be the future frontier for new imaging systems. However there are several technological barriers that need to be overcome as well as challenges in what are the best solutions perceptually. The goal of this network is to combine expertise from several disciplines as engineering, computer science, physics, vision science and psychology – usually disconnected – and train ESRs to be capable of working with all stages and aspects of visual processing to overcome existing interdisciplinary and intersectorial barriers to efficiently develop truly perceptually better visual imaging systems.
|Generate test content suitable for HDR and U-HDTV processing||Websites, patent fillings, videos etc.||2020-04-16 13:51:12|
|Report on the influence of perceptual cues to realism||Documents, reports||2020-04-16 13:51:39|
|Light field capture for test images in coding and processing||Other||2020-04-16 13:51:34|
|Project communication tools established, website online etc||Websites, patent fillings, videos etc.||2020-04-16 13:51:18|
|Public dissemination of project results, incl. JPEG and MPEG bodies||Websites, patent fillings, videos etc.||2020-04-16 13:51:23|
|Courses||Documents, reports||2020-04-16 13:51:28|
|Supervisory Board||Other||2019-07-08 11:30:57|
Take a look to the deliverables list in detail: detailed list of RealVision deliverables.
|year||authors and title||journal||last update|
Fangcheng Zhong, George Alex Koulieris, George Drettakis, Martin S. Banks, Mathieu Chambe, FrÃ©do Durand, RafaÅ‚ K. Mantiuk
published pages: 1-13, ISSN: 0730-0301, DOI: 10.1145/3355089.3356552
|ACM Transactions on Graphics (TOG) 38/6||2020-02-28|
Muhammad Shahzeb Khan gul, Michel BÃ¤tz, Joachim Keinert
Pixel-Wise Confidences for Stereo Disparities Using Recurrent Neural Networks
published pages: , ISSN: , DOI:
|British Machine Vision Conference||2020-02-28|
M. Umair Mukati, Soren Forchhammer
EPIC: Context Adaptive Lossless Light Field Compression using Epipolar Plane Images
published pages: , ISSN: , DOI:
|Data Compression Conference 2020||2020-02-20|
K. Wolski, D. Giunchi, S. Kinuwaki, P. Didyk, K. Myszkowski, A. Steed, R. K. Mantiuk
Selecting texture resolution using a taskâ€specific visibility metric
published pages: 685-696, ISSN: 0167-7055, DOI: 10.1111/cgf.13871
|Computer Graphics Forum 38/7||2020-01-28|
Sarvesh Agrawal, AdÃ¨le Simon, SÃ¸ren Bech, Klau BÃ¦rentsen, SÃ¸ren Forchhammer
Defining Immersion: Literature Review and Implications for Research on Immersive Audiovisual Experiences
published pages: , ISSN: , DOI:
Nanyang Ye, Krzysztof Wolski, Rafal K. Mantiuk
Predicting Visible Image Differences Under Varying Display Brightness and Viewing Distance
published pages: 5434-5442, ISSN: , DOI:
|The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)||2019-08-06|
Krzysztof Wolski, Daniele Giunchi, Nanyang Ye, Piotr Didyk, Karol Myszkowski, RadosÅ‚aw Mantiuk, Hans-Peter Seidel, Anthony Steed, RafaÅ‚ K. Mantiuk
Dataset and Metrics for Predicting Local Visible Differences
published pages: 1-14, ISSN: 0730-0301, DOI: 10.1145/3196493
|ACM Transactions on Graphics 37/5||2019-07-08|
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The information about "REALVISION" are provided by the European Opendata Portal: CORDIS opendata.