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

Local feature detection and description play an important role in many computer vision
tasks, which are designed to detect and describe keypoints in" any scene" and" any …

This study addresses the challenge of performing visual localization in demanding
conditions such as night-time scenarios adverse weather and seasonal changes. While …

Recent advances in mapping techniques have enabled the creation of highly accurate
dense 3D maps during robotic missions, such as point clouds, meshes, or NeRF-based …

Feature matching is crucial in visual localization, where 2D-3D correspondence plays a
major role in determining the accuracy of camera pose. A sufficient number of well …

Visual place recognition (VPR) is a task that aims to predict the location of an image based
on the existing images. Because image data can often be massive, extracting features …

Place recognition is a challenging task in computer vision, crucial for enabling autonomous
vehicles and robots to navigate previously visited environments. While significant progress …

We present a novel dataset named as HPointLoc, specially designed for exploring
capabilities of visual place recognition in indoor environment and loop detection in …

Scene coordinate regression (SCR) methods have emerged as a promising area of
research due to their potential for accurate visual localization. However, many existing SCR …

Visual relocalization is a key technique to autonomous driving, robotics, and
virtual/augmented reality. After decades of explorations, absolute pose regression (APR) …