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 …

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 …

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 …

Absolute camera pose regression methods estimate the position and orientation of a camera
by only using the captured image. A convolutional backbone with a multi-layer perceptron …

Deep learning based localization and mapping has recently attracted significant attention.
Instead of creating hand-designed algorithms through exploitation of physical models or …

We describe a learning-based system that estimates the camera position and orientation
from a single input image relative to a known environment. The system is flexible wrt the …

We tackle the problem of establishing dense pixel-wise correspondences between a pair of
images. In this work, we introduce Dual-Resolution Correspondence Networks (DualRC …

Visual localization, ie, the problem of camera pose estimation, is a central component of
applications such as autonomous robots and augmented reality systems. A dominant …

Visual Localization is one of the key enabling technologies for autonomous driving and
augmented reality. High quality datasets with accurate 6 Degree-of-Freedom (DoF) …

Abstract Masked Image Modeling (MIM) has recently been established as a potent pre-
training paradigm. A pretext task is constructed by masking patches in an input image, and …