KS-APR: Keyframe Selection for Robust Absolute Pose Regression. (arXiv:2308.05459v1 [cs.CV])

Markerless Mobile Augmented Reality (AR) aims to anchor digital content in
the physical world without using specific 2D or 3D objects. Absolute Pose
Regressors (APR) are end-to-end machine learning solutions that infer the
device's pose from a single monocular image. Thanks to their low computation
cost, they can be directly executed on the constrained hardware of mobile AR
devices. However, APR methods tend to yield significant inaccuracies for input
images that are too distant from the training set. This paper …

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