Sensor Noise Model
A Sensor Noise Model is a computational framework that characterizes the statistical deviations and distortions introduced by a physical imaging sensor during image acquisition, distinguishing itself from general noise models by specifically simulating the idiosyncratic noise patterns—such as photon shot noise, readout noise, and pixel non-uniformity—encountered in real-world vision systems, thereby enabling more robust sim-to-real transfer in vision-based machine learning applications.
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27.2K
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1.6K
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566
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2017–2026
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468
A benchmark for RGB-D visual odometry, 3D reconstruction and SLAM
Ankur Handa, Thomas J. Whelan, John McDonald et al. · 2014 · 939 citations
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Max Planck Institute for Gravitational Physics, Germany
5 publications · 157 citations
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Centre National de la Recherche Scientifique
Paris, France
14 h-index
48 publications
3.1K citations
ETH Zurich
Zurich, Switzerland
12 h-index
35 publications
3.4K citations
Massachusetts Institute of Technology
Cambridge, United States
10 h-index
19 publications
2K citations

Imperial College London
London, United Kingdom
10 h-index
27 publications
3.5K citations
University of Oxford
Oxford, United Kingdom
7 h-index
20 publications
598 citations
University of Zurich
Zurich, Switzerland
7 h-index
12 publications
1.8K citations

Beijing Institute of Technology
Beijing, China
7 h-index
23 publications
1.6K citations
Carnegie Mellon University
Pittsburgh, United States
7 h-index
17 publications
797 citations
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13 publications · 354 citations
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17 publications · 432 citations
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11 publications · 464 citations
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9 publications · 293 citations
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9 publications · 783 citations
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