Will Smith is a Professor in Computer Vision at the University of York, leading the Vision, Graphics and Learning (VGL) research group. He previously held a Royal Academy of Engineering/The Leverhulme Trust Senior Research Fellow (2019-2020) and serves as Associate Editor of Pattern Recognition . PhD in Computer Vision (2007) and BSc in Computer Science (2002), both from University of York His research bridges computer vision, graphics, and machine learning, focusing on physics-based 3D vision , shape/appearance modeling , and statistical/machine learning applications in areas like face/body analysis, surveying, object capture, and inverse rendering. Methodologically, he works with convex/nonlinear optimization, manifold learning, and computational geometry. Recent publications emphasize neural rendering (ECCV 2024), document symbol detection (ICDAR 2023), and rotation-equivariant spherical neural fields (NeurIPS 2022). These works reflect trends in 3D-aware machine learning, outdoor scene modeling, and geometrically constrained optimization. Royal Academy of Engineering/The Leverhulme Trust Senior Research Fellow (2019-2020) Associate Editor, Pattern Recognition (2019–Present) Smith supervises nine PhD students including Evgenii Kashin, James Gardner, and Tejas Pandey. He has participated in numerous service roles: Area Chair for ICCV 2023, Programme Chair for BMVC 2020, and long-term reviewer for CVPR/ICCV/ECCV conferences since 2008. His lab engages in projects like Branching Out (historic tree mapping) and Google Daydream collaborations on VR/AR head modeling.
- Computer Vision
- Computer Graphics
- Machine Learning
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