no code implementations • ECCV 2020 • Connor Henley, Tomohiro Maeda, Tristan Swedish, Ramesh Raskar
Hidden objects attenuate light that passes through the hidden space, leaving an observable signature that can be used to reconstruct their shape.
no code implementations • CVPR 2023 • Siddharth Somasundaram, Akshat Dave, Connor Henley, Ashok Veeraraghavan, Ramesh Raskar
Specifically, we study how ToF information can reduce the number of measurements and spatial resolution needed for shape reconstruction.
no code implementations • 7 Sep 2022 • Connor Henley, Siddharth Somasundaram, Joseph Hollmann, Ramesh Raskar
We propose methods that use specular, multibounce lidar returns to detect and map specular surfaces that might be invisible to conventional lidar systems that rely on direct, single-scatter returns.
no code implementations • ICCV 2021 • Tristan Swedish, Connor Henley, Ramesh Raskar
We recover high-frequency information encoded in the shadows cast by an object to estimate a hemispherical photograph from the viewpoint of the object, effectively turning objects into cameras.