Camera Relocalization
16 papers with code • 0 benchmarks • 2 datasets
"Camera relocalization, or image-based localization is a fundamental problem in robotics and computer vision. It refers to the process of determining camera pose from the visual scene representation and it is essential for many applications such as navigation of autonomous vehicles, structure from motion (SfM), augmented reality (AR) and simultaneous localization and mapping (SLAM)." (Source)
Benchmarks
These leaderboards are used to track progress in Camera Relocalization
Cambridge Landmarks
DeepLoc
Latest papers with no code
Relative Geometry-Aware Siamese Neural Network for 6DOF Camera Relocalization
6DOF camera relocalization is an important component of autonomous driving and navigation.
Hinted Networks
We present Hinted Networks: a collection of architectural transformations for improving the accuracies of neural network models for regression tasks, through the injection of a prior for the output prediction (i. e. a hint).
Scene Coordinate Regression with Angle-Based Reprojection Loss for Camera Relocalization
Image-based camera relocalization is an important problem in computer vision and robotics.
Diversity in Machine Learning
Even though the diversity plays an important role in machine learning process, there is no systematical analysis of the diversification in machine learning system.
Full-Frame Scene Coordinate Regression for Image-Based Localization
In this paper, instead of in a patch-based manner, we propose to perform the scene coordinate regression in a full-frame manner to make the computation efficient at test time and, more importantly, to add more global context to the regression process to improve the robustness.
Exploiting Points and Lines in Regression Forests for RGB-D Camera Relocalization
Camera relocalization plays a vital role in many robotics and computer vision tasks, such as global localization, recovery from tracking failure and loop closure detection.
Towards CNN map representation and compression for camera relocalisation
This paper presents a study on the use of Convolutional Neural Networks for camera relocalisation and its application to map compression.
Camera Relocalization by Computing Pairwise Relative Poses Using Convolutional Neural Network
The camera location for the query image is obtained via triangulation from two relative translation estimates using a RANSAC based approach.
Towards CNN Map Compression for camera relocalisation
We use a CNN map representation and introduce the notion of CNN map compression by using a smaller CNN architecture.
On-the-Fly Adaptation of Regression Forests for Online Camera Relocalisation
Camera relocalisation is an important problem in computer vision, with applications in simultaneous localisation and mapping, virtual/augmented reality and navigation.
