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20182024
most citedSemantically Accurate Super-Resolution Generative Adversarial Networks

1 citations · 1 across the 6 of their papers we have counts for

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cs.RO2024

Mixing Data-driven and Geometric Models for Satellite Docking Port State Estimation using an RGB or Event Camera

Cedric Le Gentil, Jack Naylor, Nuwan Munasinghe +5

In-orbit automated servicing is a promising path towards lowering the cost of satellite operations and reducing the amount of orbital debris. For this purpose, we present a pipelin…

cs.RO2022

NOCaL: Calibration-Free Semi-Supervised Learning of Odometry and Camera Intrinsics

Ryan Griffiths, Jack Naylor, Donald G. Dansereau

There are a multitude of emerging imaging technologies that could benefit robotics. However the need for bespoke models, calibration and low-level processing represents a key barri…

cs.RO2022

BuFF: Burst Feature Finder for Light-Constrained 3D Reconstruction

Ahalya Ravendran, Mitch Bryson, Donald G. Dansereau

Robots operating at night using conventional vision cameras face significant challenges in reconstruction due to noise-limited images. Previous work has demonstrated that burst-ima…

cs.RO2021

Burst Imaging for Light-Constrained Structure-From-Motion

Ahalya Ravendran, Mitch Bryson, Donald G. Dansereau

Images captured under extremely low light conditions are noise-limited, which can cause existing robotic vision algorithms to fail. In this paper we develop an image processing tec…

cs.RO2021

Refractive Light-Field Features for Curved Transparent Objects in Structure from Motion

Dorian Tsai, Peter Corke, Thierry Peynot +1

Curved refractive objects are common in the human environment, and have a complex visual appearance that can cause robotic vision algorithms to fail. Light-field cameras allow us t…

cs.RO2021

Unsupervised Learning of Depth Estimation and Visual Odometry for Sparse Light Field Cameras

S. Tejaswi Digumarti, Joseph Daniel, Ahalya Ravendran +1

While an exciting diversity of new imaging devices is emerging that could dramatically improve robotic perception, the challenges of calibrating and interpreting these cameras have…