Onur G. Guleryuz
Onur G. Guleryuz is a Software Engineer at Google working on machine learning and computer vision problems with applications in augmented and virtual reality. Prior to Google he worked at LG Electronics, Futurewei, NTT DoCoMo, and Seiko-Epson all in Silicon Valley. Before coming to Silicon Valley in 2000 he served as an Asst. Prof. with NYU Tandon School of Engineering in New York.
His research interests include topics in machine learning, signal processing, computer vision, and information theory. He has served in numerous panels, conference committees, and media-related industry standardization bodies. He has authored an extensive number of refereed papers, granted US patents, and has leading edge contributions to products ranging from mobile phones to displays and printers. He has been an active member of IEEE Signal Processing Society, having served as chair of the IEEE Signal Processing Society Image, Video, and Multidimensional Signal Processing Technical Committee (IVMSP TC) and as a member of the IEEE Signal Processing Society Multimedia Signal Processing Technical Committee (MMSP TC) .
He received the BS degrees in electrical engineering and physics from Bogazici University, Istanbul, Turkey in 1991, the M.S. degree in engineering and applied science from Yale University, New Haven, CT in 1992, and the Ph.D. degree in electrical engineering from University of Illinois at Urbana-Champaign (UIUC), Urbana, in 1997.
He received the National Science Foundation Career Award, the IEEE Signal Processing Society Best Paper Award, the IEEE International Conference on Image Processing Best Paper Award, the Seiko-Epson Corporation President's Award for Research and Development, and the DoCoMo Communications Laboratories President's Award for Research. He is a Fellow of IEEE.
Further information including patent and publication details can be found here.
Authored Publications
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Google
Sandwiched Compression: Repurposing Standard Codecs with Neural Network Wrappers
Phil A. Chou
Hugues Hoppe
Danhang Tang
Jonathan Taylor
Philip Davidson
arXiv:2402.05887 (2024)
Sandwiched Video Compression: An Efficient Learned Video Compression Approach
Danhang "Danny" Tang
Jonathan Taylor
Phil Chou
IEEE International Conference on Image Processing (2023)
Sandwiched Image Compression: Increasing the resolution and dynamic range of standard codecs
Phil Chou
Hugues Hoppe
Danhang "Danny" Tang
Philip Davidson
2022 Picture Coding Symposium (PCS), IEEE (to appear)
Sandwiched Image Compression: Wrapping Neural Networks Around a Standard Codec
Phil Chou
Hugues Hoppe
Danhang "Danny" Tang
Philip Davidson
2021 IEEE International Conference on Image Processing (ICIP), IEEE, Anchorage, Alaska, pp. 3757-3761
Deep Implicit Volume Compression
Danhang "Danny" Tang
Phil Chou
Christian Haene
Mingsong Dou
Jonathan Taylor
Shahram Izadi
Sofien Bouaziz
Cem Keskin
CVPR (2020)
Fast Lifting for 3D Hand Pose Estimation in AR/VR Applications
Christine Kaeser-Chen
IEEE International Conference on Image Processing, 2018 (2018)
Depth from motion for smartphone AR
Julien Valentin
Neal Wadhwa
Max Dzitsiuk
Michael John Schoenberg
Vivek Verma
Ambrus Csaszar
Ivan Dryanovski
Joao Afonso
Jose Pascoal
Konstantine Nicholas John Tsotsos
Mira Angela Leung
Mirko Schmidt
Sameh Khamis
Vladimir Tankovich
Shahram Izadi
Christoph Rhemann
ACM Transactions on Graphics (2018)
