2021
DOI: 10.48550/arxiv.2104.08278
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

Fusing the Old with the New: Learning Relative Camera Pose with Geometry-Guided Uncertainty

Abstract: Learning methods for relative camera pose estimation have been developed largely in isolation from classical geometric approaches. The question of how to integrate predictions from deep neural networks (DNNs) and solutions from geometric solvers, such as the 5-point algorithm [37], has as yet remained under-explored. In this paper, we present a novel framework that involves probabilistic fusion between the two families of predictions during network training, with a view to leveraging their complementary benefi… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Publication Types

Select...

Relationship

0
0

Authors

Journals

citations
Cited by 0 publications
references
References 76 publications
0
0
0
Order By: Relevance

No citations

Set email alert for when this publication receives citations?