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

Visual localization is a fundamental task for various applications including autonomous
driving and robotics. Prior methods focus on extracting large amounts of often redundant …

Deep learning has achieved impressive results in camera localization, but current single-
image techniques typically suffer from a lack of robustness, leading to large outliers. To …

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) …

We present a simple baseline for directly estimating the relative pose (rotation and
translation, including scale) between two images. Deep methods have recently shown …

Deep-learning-based localization and mapping approaches have recently emerged as a
new research direction and receive significant attention from both industry and academia …

Temporal camera relocalization estimates the pose with respect to each video frame in
sequence, as opposed to one-shot relocalization which focuses on a still image. Even …

Previous methods solve feature matching and pose estimation using a two-stage process by
first finding matches and then estimating the pose. As they ignore the geometric …

Monocular Re-Localization (MRL) is an essential component in autonomous applications,
estimating 6 degree-of-freedom ego poses wrt the scene map using monocular images …

We propose to construct a view graph to excavate the information of the whole given
sequence for absolute camera pose estimation. Specifically, we harness GNNs to model the …