Learning 2D-3D Correspondences To Solve The Blind Perspective-n-Point Problem

Understand

Conventional absolute camera pose via a Perspective-n-Point (PnP) solver often assumes that the correspondences between 2D image pixels and 3D points are given.

• When the correspondences between 2D and 3D points are not known a priori, the task becomes the much more challenging blind PnP problem.
• This paper proposes a deep CNN model which simultaneously solves for both the 6-DoF absolute camera pose and 2D--3D correspondences.
• Our model comprises three neural modules connected in sequence.