Marco Lops (Fellow, IEEE) received the Laurea and Ph.D. degree from “Federico II” University. Previously, he was an Assistant Professor and then became an Associate Professor with the University of Naples Federico II. In March 2000, he moved to the University of Cassino and Southern Lazio as a Full Professor and he returned to the University of Naples Federico II in 2018. From 2009 to 2012, he was also with ENSEEIHT, Toulouse, France, first as a Full Professor (on leave of absence from Italy) and then as a Visiting Professor. In Fall 2008, he was a Visiting Professor with the University of Minnesota and Columbia University, in Spring 2009. Previously, he had also held visiting positions with the University of Connecticut, Rice University, and Princeton University. He is currently a Professor with the Department of Electrical and Information Technology (DIETI), University of Naples Federico II, Italy. He has authored or co-authored more than 90 scientific papers published on refereed journals. His research interests include detection and estimation, with emphasis on communications and radar signal processing. He was a co-recipient (with Ezio Biglieri) of the 2014 Best Paper Award from the Journal of Communications and Networks. From 2009 to 2015, he served two terms for the Sensor Array and Multichannel Signal Processing Technical Committee (SAM). He has served as an Associate Editor for the Journal of Communications and Networks, IEEE Transactions on Information Theory (Area: Detection and Estimation, two terms), IEEE Signal Processing Letters, and IEEE Transactions on Signal Processing (two terms). He also served as a Senior Area Editor for IEEE Transactions on Signal Processing. He was selected to serve as a Distinguished Lecturer for the Signal Processing Society from 2018 to 2020.

Dr. Frederic Dufaux is a CNRS Research Director at Université Paris-Saclay, CNRS, CentraleSupélec, Laboratoire des Signaux et Systèmes (L2S, UMR 8506), where he is head of the Telecom and Networking research hub. He is a Fellow of IEEE.
Frederic received the M.Sc. in physics and Ph.D. in electrical engineering from the Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland, in 1990 and 1994 respectively. He has over 30 years of experience in research, previously holding positions at EPFL, Emitall Surveillance, Genimedia, Compaq, Digital Equipment, and MIT.
Frederic was Vice General Chair of ICIP 2014, General Chair of MMSP 2018, and Technical Program co-Chair of ICIP 2019 and ICIP 2021. He is Technical Program co-Chair of ICIP 2025 and MMSP 2025, and General Chair of ICME 2026. He served as Chair of the IEEE SPS Multimedia Signal Processing (MMSP) Technical Committee in 2018 and 2019. He was a member of the IEEE SPS Technical Directions Board from 2018 to 2021. He was Chair of the Steering Committee of ICME in 2022 and 2023. Since 2025, he is IEEE SPS Vice President Technical Directions, and member of the IEEE SPS Board of Governors and Executive Committee. He was also a founding member and the Chair of the EURASIP Technical Area Committee on Visual Information Processing from 2015 to 2021.
He was Editor-in-Chief of Signal Processing: Image Communication from 2010 until 2019. Since 2021, he is Specialty Chief Editor of the section on Image Processing in the journal Frontiers in Signal Processing.
In 2022, he received the EURASIP Meritorious Service Award, “for his leadership and contributions for the development of visual information processing within EURASIP”.
Frederic is on the Executive Board of Systematic Paris-Region since 2019, a European competitiveness cluster which brings together and drives an ecosystem of excellence in digital technologies and DeepTech.
He has been involved in the standardization of digital video and imaging technologies for more than 15 years, participating both in the MPEG and JPEG committees. He was co-chairman of JPEG 2000 over wireless (JPWL) and co-chairman of JPSearch. He is the recipient of two ISO awards for these contributions.
His research interests include image and video coding, 3D video, high dynamic range imaging, visual quality assessment, video surveillance, privacy protection, image and video analysis, multimedia content search and retrieval, video transmission over wireless network. He is author or co-author of 3 books, more than 250 research publications (h-index=53, 11000+ citations) and more than 25 patents issued or pending. He is in the « World’s Top 2% Scientists » list from Stanford University.

Speech Title: Towards hyper-realistic and immersive visual communications

Abstract: Nowadays, thanks to rapid technological progresses over the last decades, digital images and video sequences are ubiquitous, with many remarkable and successful applications and services. A key driver to research and development activities has been the objective to provide an ever-improving visual quality and user experience.
In this context, one of the next frontiers is to be able to faithfully represent the physical world and to deliver a perceptually hyperrealist and immersive visual experience. On the one hand, the human visual system is able to perceive a wide range of colors, luminous intensities, and depth, as present in a real scene. However, current traditional imaging technologies cannot capture nor reproduce such a rich visual information. On the other hand, immersive applications aim at giving to the user the sense of being present and immersed in one location or environment, without being physically there.
Recent research innovations have made it possible to address current bottlenecks in multimedia systems. As a result, new multimedia signal processing areas have emerged such as ultra-high definition, high dynamic range imaging, light fields, and point clouds. These technologies have the potential to bring a leap forward for upcoming multimedia systems. However, the effective deployment of hyper-realistic video technologies entails many technical and scientific challenges.
In this talk, I will discuss a few recent research activities related to hyper-realistic and immersive imaging. I will first consider point clouds, a very promising type of representation. One major distinguishing feature of point clouds is that, unlike images, they do not have a regular structure. Moreover, they can also be very sparse. For these reasons, point cloud processing presents significant challenges. Here, I will present recent learning-based approaches for point cloud compression and quality assessment. In a second phase, I will discuss high dynamic range imaging and in particular tone mapping operators (TMO). TMOs are used to compress the dynamic range with the aim of preserving the perceptual cues of the scene. Here, I will show how we can leverage semantic information as well as contextual cues from the scene to drive a TMO in a way similar to how expert photographers retouch images.

 

Prof. Ali Mohammad-Djafari, France
Former Research Director at CNRS, France
Shaoxing University, Zhejiang, China
IDT-EIT, Ningbo, Zhejiang, China