Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: LiDAR Lateral Localisation Despite Challenging Occlusion from Traffic   This paper presents a system for improving the robustness of LiDAR lateral
localisation systems. This is made possible by including detections of road
boundaries which are invisible to the sensor (due to occlusion, e.g. traffic)
but can be located by our Occluded Road Boundary Inference Deep Neural Network.
We show an example application in which fusion of a camera stream is used to
initialise the lateral localisation. We demonstrate over four driven forays
through central Oxford - totalling 40 km of driving - a gain in performance
that inferring of occluded road boundaries brings.

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The categories of this paper are: dg-ga
10
The categories of this paper are: q-bio
30
The categories of this paper are: q-alg
33
The categories of this paper are: plasm-ph
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The categories of this paper are: eess
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The categories of this paper are: q-fin
3
The categories of this paper are: physics
32
The categories of this paper are: atom-ph
9
The categories of this paper are: nlin
27
The categories of this paper are: comp-gas
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The categories of this paper are: nucl-ex
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The categories of this paper are: patt-sol
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The categories of this paper are: adap-org
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The categories of this paper are: supr-con
12
The categories of this paper are: nucl-th
6
The categories of this paper are: astro-ph