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Seminar abstract

Neural Modeling and Rendering: A Paradigm Shift in Computer Vision and Graphics

Jingyi Yu
Professor
School of Information Science and Technology, ShanghaiTech University


Abstract: Traditional computer graphics conducts accurate simulations by explicitly modeling surface geometry, surface reflectance and lighting via the rendering equation. They manage to produce high quality rendering but at an ultra-high computational cost. Conversely, traditional computer vision, in particular 3D reconstruction, seeks to recover camera pose, scene geometry, surface reflectance, etc, from the imagery data via techniques such as correspondence matching and bundle adjustment. In this talk, I present our recent efforts on employing neural modeling and rendering techniques to overcome the limitations in traditional rendering and 3D reconstruction. For graphics I demonstrate deep learning techniques that tackle unknown surface reflectance, corrupted/incomplete 3D shape, and volumetric opacity to produce unprecedented visual quality. For vision, I present a novel volumetric neural reconstruction framework that significantly outperforms state-of-the-art structure-from-motion and photometric stereo methods in reconstruction accuracy. Finally, I discuss how such neural representations may fundamentally change computer vision and graphics and potentially lead to a paradigm shift.

Bio: Jingyi Yu is currently Vice Provost of ShanghaiTech University, Professor and Executive Dean of the School of Information Science and Technology. He received B.S. from Caltech in 2000 and Ph.D. from MIT in 2005. He has published over 140 papers at highly refereed conferences and journals, and holds over 20 international patents on computer vision and computational imaging. He is a recipient of the NSF CAREER Award and has organized many international conferences in computer vision. He is a member of Shanghai Al Advisory Committee, and co-founder of DGene. He has been an Associate Editor of IEEE TPAMI, IEEE TIP, and Elsevier CVIU. He was a program chair of ICCP 2016, ICPR 2020 and WACV 2021, and will be a program chair of two top Al conferences, IEEE CVPR 2021 and ICCV 2025.
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