2 citations · 3 across the 3 of their papers we have counts for
9 papers
Spline Sketches: An Efficient Approach for Photon Counting Lidar
Michael Patrick Sheehan, Julian Tachella, Mike E. Davies
Photon counting lidar has become an invaluable tool for 3D depth imaging due to the fine-precision it can achieve over long ranges. However, high frame rate, high resolution lidar…
Imaging with Equivariant Deep Learning
Dongdong Chen, Mike Davies, Matthias J. Ehrhardt +3
From early image processing to modern computational imaging, successful models and algorithms have relied on a fundamental property of natural signals: symmetry. Here symmetry refe…
Sketched RT3D: How to reconstruct billions of photons per second
Julián Tachella, Michael P. Sheehan, Mike E. Davies
Single-photon light detection and ranging (lidar) captures depth and intensity information of a 3D scene. Reconstructing a scene from observed photons is a challenging task due to…
Surface Detection for Sketched Single Photon Lidar
Michael P. Sheehan, Julián Tachella, Mike E. Davies
Single-photon lidar devices are able to collect an ever-increasing amount of time-stamped photons in small time periods due to increasingly larger arrays, generating a memory and c…
Equivariant Imaging: Learning Beyond the Range Space
Dongdong Chen, Julián Tachella, Mike E. Davies
In various imaging problems, we only have access to compressed measurements of the underlying signals, hindering most learning-based strategies which usually require pairs of signa…
Robust 3D reconstruction of dynamic scenes from single-photon lidar using Beta-divergences
Quentin Legros, Julian Tachella, Rachael Tobin +6
In this paper, we present a new algorithm for fast, online 3D reconstruction of dynamic scenes using times of arrival of photons recorded by single-photon detector arrays. One of t…