Augmented reality (AR) has proven to be an invaluable interactive medium to reduce
cognitive load by bridging the gap between the task-at-hand and relevant information by …

Recent years have witnessed enormous progress in AI-related fields such as computer
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …

Camera pose estimation in known scenes is a 3D geometry task recently tackled by multiple
learning algorithms. Many regress precise geometric quantities, like poses or 3D points …

Robust and accurate visual localization is a fundamental capability for numerous
applications, such as autonomous driving, mobile robotics, or augmented reality. It remains …

We introduce GNeRF, a framework to marry Generative Adversarial Networks (GAN) with
Neural Radiance Field (NeRF) reconstruction for the complex scenarios with unknown and …

We introduce a comprehensive benchmark for local features and robust estimation
algorithms, focusing on the downstream task—the accuracy of the reconstructed camera …

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 …

We describe a data-driven method for inferring the camera viewpoints given multiple images
of an arbitrary object. This task is a core component of classic geometric pipelines such as …

We seek to predict the 6 degree-of-freedom (6DoF) pose of a query photograph with respect
to a large indoor 3D map. The contributions of this work are three-fold. First, we develop a …

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 …