With the ubiquity of advanced web technologies and location-sensing hand held devices,
citizens regardless of their knowledge or expertise, are able to produce spatial information …

In this paper, we propose a survey of the Simultaneous Localization And Map** (SLAM)
field when considering the recent evolution of autonomous driving. The growing interest …

The overall objective of this work is to review the assistive technologies that have been
proposed by researchers in recent years to address the limitations in user mobility posed by …

Visual localization is the task of accurate camera pose estimation in a known scene. It is a
key problem in computer vision and robotics, with applications including self-driving cars …

In recent years visual place recognition (VPR), ie, the problem of recognizing the location of
images, has received considerable attention from multiple research communities, spanning …

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 …

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 …

Novel view synthesis is a long-standing problem. In this work, we consider a variant of the
problem where we are given only a few context views sparsely covering a scene or an …

Visual SLAM (simultaneous localization and map**) refers to the problem of using
images, as the only source of external information, in order to establish the position of a …