IEEE 9th International Conference on Multimedia Information Processing and Retrieval (MIPR 2026) IEEE MIPR 2026
August 9–11, 2026 | Chatrium Grand Bangkok Hotel, Thailand
Since 1997, our exploration has been fueled by the ambition to reconstruct 3D worlds from large-scale multi-view camera arrays, giving birth to “free-viewpoint video.” For over two decades, we have refined the foundational pillars of multi-view geometry, such as camera calibration and SLAM. However, we are now entering a transformative “Next Era” where the synergy between these traditional methodologies and modern AI is redefining the boundaries of what is possible.
In this talk, I will present our journey as it evolves from early 50-camera setups to the cutting edge of AI-driven 3D vision. I will discuss how recent breakthroughs in neural rendering and generative video intelligence are unleashing the true potential of multi-view systems—moving beyond mere geometric reconstruction toward deep "Spatial Intelligence."
While these technologies have found impactful applications in fields like surgical scene analysis and Medical AR, their potential extends far beyond, promising a future where AI can perceive, understand, and interact with complex 3D environments in real-time. I will introduce our latest research projects and share my excitement for this new chapter in computer vision, where multi-view analysis serves as the cornerstone for the next generation of intelligent systems.
Hideo Saito received his Ph.D. in Electrical Engineering from Keio University, Japan, in 1992. He has been a faculty member at Keio University since then and has served as a Full Professor since 2006. From 1997 to 1999, he was a Visiting Researcher at the Robotics Institute, Carnegie Mellon University, contributing to the pioneering "Virtualized Reality" project.
He currently holds key academic leadership positions at Keio University, serving as the Chair of the School of Informatics, Management, and Human Sciences in the Graduate School of Science and Technology, as well as a Group Leader at the AI Computing and Research Center within the Keio University Global Research Institute (KGRI).
His research expertise lies in 3D computer vision and scene analysis, with a current focus on the synergy between multi-view geometry and modern AI technologies. His work spans a wide range of high-impact applications, including Augmented Reality (AR), Mixed Reality (MR), and advanced surgical scene analysis.
Dr. Saito has a distinguished record of leadership in the global academic community, having served as Program Chair for ACCV 2014, General Chair for ISMAR 2015, Program Chair for ISMAR 2016, and Scientific Program Chair for Euro VR 2020. He is a Fellow of the Institute of Electronics, Information and Communication Engineers (IEICE) and the Virtual Reality Society of Japan (VRSJ).
In addition to his university leadership, he currently serves as the President of the Institute of Image Information and Television Engineers (ITE) and is the former President of the Information and Systems Society of IEICE. His extensive contributions have been recognized with numerous accolades, including the prestigious Best Journal Paper Award at ISMAR 2023.
Professor Mohan Kankanhalli, Director of NUS AI Institute, currently holds the distinguished position of Provost’s Chair Professor of Computer Science. He is also the Deputy Executive Chairman (Talent) of AI Singapore, which is Singapore's national AI R&D program. He was formerly the Dean of NUS School of Computing during 2016-2022. Before becoming the Dean, he was the NUS Vice Provost (Graduate Education) during 2014-2016 and Associate Provost (Graduate Education) during 2011-2013. Earlier, he was the Vice-Dean for Academic Affairs & Graduate Studies at the NUS School of Computing during 2008-2010 and Vice-Dean for Research during 2001-2007.
Prof. Kankanhalli’s research interests are in Multimodal Computing, Computer Vision and Trustworthy AI. He has made fundamental contributions in the areas of image and video understanding, visual saliency and trustworthy AI. He is the Associate Editor-in-Chief of IEEE Multimedia magazine. He is on the editorial boards of Springer Multimedia Systems and Springer Journal on Big Data.
Prof. Kankanhalli was a member of World Economic Forum's 2023-2024 Global Future Council on the Future of Artificial Intelligence. He is a member of ACM’s Global Technology Policy Council. He is a Fellow of IEEE, IAPR and ACM.
Tülay Adali received the Ph.D. degree in Electrical Engineering from North Carolina State University, Raleigh, NC, USA, in 1992 and joined the faculty at the University of Maryland Baltimore County (UMBC), Baltimore, MD, the same year. She is currently a Distinguished University Professor in the Department of Computer Science and Electrical Engineering at UMBC and is the director of the Machine Learning for Signal Processing Lab (MLSP Lab).
Prof. Adali assisted in the organization of a number of international conferences and workshops including the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), the IEEE International Workshop on Neural Networks for Signal Processing (NNSP), and the IEEE International Workshop on Machine Learning for Signal Processing (MLSP). She was the General Co-Chair, NNSP (2001–2003), MLSP 2023, Technical Chair, MLSP (2004–2008); Program Chair, MLSP (2008, 2009, and 2014), International Conference on Independent Component Analysis and Source Separation (2009); Publicity Chair, ICASSP (2000 and 2005); and Publications Chair, ICASSP 2008. She was the Technical Program Co-Chair for ICASSP 2017 and Special Sessions Chair for ICASSP 2018, ICASSP 2024, and EUSIPCO 2020. She is the Technical Program and Workshops Co-Chair for ICASSP 2026.
Prof. Adali is currently the editor-in-chief of the Signal Processing Magazine, and has served as the Chair of the IEEE Brain Technical Community, and Vice President-Technical Directions of the IEEE Signal Processing Society (SPS) for the period 2019-2022. She chaired the IEEE SPS MLSP Technical Committee (2003–2005, 2011–2013), and served or currently serving on a number of committees/boards including the SPS Conference Board (1998–2006, 2017-Present), IEEE SPS Fellow Reference Committee (2011-2014), IEEE SPS Signal Processing Theory and Methods (2010-2015) Technical Committee, and the IEEE SPS Bio Imaging and Signal Processing Technical Committee (2004–2007, 2018-Present). She was an Associate Editor for IEEE Transactions on Signal Processing (2003–2006), IEEE Transactions on Biomedical Engineering (2007–2013), IEEE Journal of Selected Areas in Signal Processing (2010-2013), and Elsevier Signal Processing Journal (2007–2010), and served on the Editorial Board of the Proceedings of the IEEE (2013-2019). She is currently serving on the Senior Editorial Board of IEEE Journal of Selected Topics in Signal Processing and the Editorial Board of Journal of Signal Processing Systems for Signal, Image, and Video Technology.
Prof. Adali is a Fellow of the IEEE, AIMBE, AAIA, a Fulbright Scholar, and an IEEE Signal Processing Society Distinguished Lecturer. She is the recipient of a 2020 Humboldt Research Award, 2013 University System of Maryland Regents' Award for Research, an NSF CAREER Award, and a number of paper awards including the 2010 IEEE Signal Processing Society Best Paper Award. Her current research interests are in the areas of statistical signal processing, machine learning, and applications in medical image analysis and fusion.