Virtual reality, augmented reality, robotics, and autonomous driving, have recently attracted
much attention from both academic and industrial communities, in which image-based …

Unlike its image based counterpart, point cloud based retrieval for place recognition has
remained as an unexplored and unsolved problem. This is largely due to the difficulty in …

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 …

Maps are a key component in image-based camera localization and visual SLAM systems:
they are used to establish geometric constraints between images, correct drift in relative …

In this work we propose a new CNN+ LSTM architecture for camera pose regression for
indoor and outdoor scenes. CNNs allow us to learn suitable feature representations for …

Accurately determining the position and orientation from which an image was taken, ie,
computing the camera pose, is a fundamental step in many Computer Vision applications …

Camera localization involves the estimation of the camera pose of an image from a random
scene. We used a single image or sequence of images or videos as the input. The output …

We address the task of estimating camera parameters from a set of images depicting a
scene. Popular feature-based structure-from-motion (SfM) tools solve this task by …

We tackle the problem of large scale visual place recognition, where the task is to quickly
and accurately recognize the location of a given query photograph. We present the following …

Is it possible to determine the location of a photo from just its pixels? While the general
problem seems exceptionally difficult, photos often contain cues such as landmarks, weather …