We address the problem of inferring the pose of an RGB-D camera relative to a known 3D
scene, given only a single acquired image. Our approach employs a regression forest that is …

We are surrounded by plenty of information about our environment. From these multiple
sources, numerous data could be extracted: set of images, 3D model, coloured points …

We introduce the problem of scene viewpoint recognition, the goal of which is to classify the
type of place shown in a photo, and also recognize the observer's viewpoint within that …

We present a fast, simple location recognition and image localization method that leverages
feature correspondence and geometry estimated from large Internet photo collections. Such …

The field-of-view of standard cameras is very small, which is one of the main reasons that
contextual information is not as useful as it should be for object detection. To overcome this …

We introduce an efficient camera relocalization approach which can be easily integrated into
real-time 3D reconstruction methods, such as KinectFusion. Our approach makes use of …

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 …

Recovery from tracking failure is essential in any simultaneous localization and tracking
system. In this context, we explore an efficient keyframe-based relocalization method based …

In this paper we present a new method, Feature Co-occurrence Maps, for appearance-
based localisation over the course of a day. We show that by quantising local features in …

Single image super-resolution (SR) aims to estimate a high-resolution (HR) image from a
low-resolution (LR) input. Image priors are commonly learned to regularize the, otherwise …