Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Single View Geocentric Pose in the Wild   Current methods for Earth observation tasks such as semantic mapping, map
alignment, and change detection rely on near-nadir images; however, often the
first available images in response to dynamic world events such as natural
disasters are oblique. These tasks are much more difficult for oblique images
due to observed object parallax. There has been recent success in learning to
regress geocentric pose, defined as height above ground and orientation with
respect to gravity, by training with airborne lidar registered to satellite
images. We present a model for this novel task that exploits affine invariance
properties to outperform state of the art performance by a wide margin. We also
address practical issues required to deploy this method in the wild for
real-world applications. Our data and code are publicly available.

15
The categories of this paper are: nucl-ex
33
The categories of this paper are: plasm-ph
34
The categories of this paper are: chem-ph
30
The categories of this paper are: q-alg
19
The categories of this paper are: eess
5
The categories of this paper are: gr-qc
17
The categories of this paper are: q-fin
2
The categories of this paper are: math
35
The categories of this paper are: mtrl-th
3
The categories of this paper are: physics
9
The categories of this paper are: nlin
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The categories of this paper are: solv-int
7
The categories of this paper are: hep-th
29
The categories of this paper are: funct-an
10
The categories of this paper are: q-bio
31
The categories of this paper are: ao-sci