Maxx Wu
I'm a Computer Science MSc candidate at the University of Toronto, co-advised by David Lindell and Kyros Kutulakos.
I work with the Toronto Computational Imaging Group within the Dynamic Graphics Project (DGP).
My research lies at the intersection of Machine Learning and Computational Imaging, with a focus on active imaging for 3D reconstruction.
I am particularly interested in implicit neural representations, inverse rendering, and imaging.
I received my BASc in Engineering Science at the Univetsity of Toronto, specializing in Machine Intelligence. I conducted my undergraduate thesis with the Biophotonics Group advised by Ofer Levi.
My work focused on remote human vital sign measurement using IR and depth cameras.
I previously interned at ModiFace as an AR application developer.
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TurboSL: Dense, Accurate and Fast 3D by Neural Inverse Structured Light
Parsa Mirdehghan, Maxx Wu, Wenzhen Chen, David B. Lindell, Kiriakos N. Kutulakos
CVPR, 2024
project page
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video
We show how to turn a noisy and fragile active triangulation technique—three-pattern structured light with a grayscale camera—into a fast and powerful tool for 3D capture: able to output sub-pixel accurate disparities at megapixel resolution, along with reflectance, normals, and a no-reference estimate of its own pixelwise 3D error.
We use TurboSL to reconstruct a variety of complex scenes from images captured at up to 60 fps with a camera and a common projector. Our experiments highlight TurboSL’s potential for dense and highly-accurate 3D acquisition from data captured in fractions of a second.
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