We present a robust and real-time monocular six degree of freedom relocalization system.
Our system trains a convolutional neural network to regress the 6-DOF camera pose from a …

Deep learning has shown to be effective for robust and real-time monocular image
relocalisation. In particular, PoseNet is a deep convolutional neural network which learns to …

We propose a new deep learning based approach for camera relocalization. Our approach
localizes a given query image by using a convolutional neural network (CNN) for first …

We address the problem of estimating the pose of a cam-era relative to a known 3D scene
from a single RGB-D frame. We formulate this problem as inversion of the generative …

We present a robust and real-time monocular six degree of freedom visual relocalization
system. We use a Bayesian convolutional neural network to regress the 6-DOF camera pose …

Temporal camera relocalization estimates the pose with respect to each video frame in
sequence, as opposed to one-shot relocalization which focuses on a still image. Even …

Recent advances in camera relocalization use predictions from a regression forest to guide
the camera pose optimization procedure. In these methods, each tree associates one pixel …

We propose to leverage the local information in a image sequence to support global camera
relocalization. In contrast to previous methods that regress global poses from single images …

Convolutional Neural Networks (CNNs) have been applied to camera relocalization, which
is to infer the pose of the camera given a single monocular image. However, there are still …

Camera re-localization is an important but challenging task in applications like robotics and
autonomous driving. Recently, retrieval-based methods have been considered as a …