# Euler angles based loss function for camera relocalization with Deep learning

arXiv: https://arxiv.org/abs/1802.08851 · HTML: https://mlsanity.com/paper/1802.08851/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Feb 2018.

## Built on by (most cited first, 1 of 1)

- [CGA-PoseNet: Camera Pose Regression via a 1D-Up Approach to Conformal Geometric Algebra](https://mlsanity.com/paper/2302.05211/) (2023)

## Abstract (arXiv)

Deep learning has been applied to camera relocalization, in particular, PoseNet and its extended work are the convolutional neural networks which regress the camera pose from a single image. However there are many problems, one of them is expensive parameter selection. In this paper, we directly explore the three Euler angles as the orientation representation in the camera pose regressor. There is no need to select the parameter, which is not tolerant in the previous works. Experimental results on the 7 Scenes datasets and the King's College dataset demonstrate that it has competitive performances.