This plenary presentation was delivered at the Electronic Imaging Symposium held in Burlingame, CA over 2-6 February 2025. For more information see: https://ift.tt/Cdbs8a0
Title: Imaging in the Age of Artificial Intelligence
Abstract: AI is revolutionizing imaging, transforming how we capture, enhance, and experience visual content. Advancements in machine learning are enabling mobile phones to have far better cameras, enabling capabilities like enhanced zoom, state-of-the-art noise reduction, blur mitigation, and post-capture capabilities such as intelligent curation and editing of your photo collections, directly on device.
This talk will delve into some of these breakthroughs, and describe a few of the latest research directions that are pushing the boundaries of image restoration and generation, pointing to a future where AI empowers us to better capture, create, and interact with visual content in unprecedented ways.
Speaker: Peyman Milanfar, Distinguished Scientist, Google (United States)
Biography: Peyman Milanfar is a Distinguished Scientist at Google, where he leads the Computational Imaging team. Prior to this, he was a Professor of Electrical Engineering at UC Santa Cruz for 15 years, two of those as Associate Dean for Research. From 2012-2014 he was on leave at Google-x, where he helped develop the imaging pipeline for Google Glass. Over the last decade, Peyman's team at Google has developed several core imaging technologies that are used in many products. Among these are the zoom pipeline for the Pixel phones, which includes the multi-frame super-resolution ("Super Res Zoom") pipeline, and several generations of state of the art digital upscaling algorithms. Most recently, his team led the development of the "Photo Unblur" feature launched in Google Photos for Pixel devices.
Peyman received his undergraduate education in electrical engineering and mathematics from the UC Berkeley and his MS and PhD in electrical engineering from MIT. He holds more than two dozen patents and founded MotionDSP, which was acquired by Cubic Inc. Along with his students and colleagues, he has won multiple best paper awards for introducing kernel regression in imaging, the RAISR upscaling algorithm, NIMA: neural image quality assessment, and Regularization by Denoising (RED). He's been a Distinguished Lecturer of the IEEE Signal Processing Society and is a Fellow of IEEE "for contributions to inverse problems and super-resolution in imaging".
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