Visual SLAM (VSLAM) has been developing rapidly due to its advantages of low-cost
sensors, the easy fusion of other sensors, and richer environmental information. Traditional …

The Simultaneous Localization and Mapping (SLAM) technique has achieved astonishing
progress over the last few decades and has generated considerable interest in the …

Simultaneous localization and mapping (SLAM) is the process of constructing a global
model of an environment from local observations of it; this is a foundational capability for …

Inspired by properties of semantic segmentation, in this paper we investigate how to
leverage robust image segmentation in the context of privacy-preserving visual localization …

Simultaneous localization and mapping (SLAM) is crucial for the progression of autonomous
systems, including autonomous driving, augmented reality (AR), and robotics. Traditionally …

The assumption of a static environment is typical in many visual simultaneous localization
and mapping (VSLAM) systems. However dynamic objects in open scenes will mislead …

The visual SLAM in dynamic environment has been regarded as a fundamental task for
robots. Currently, existing works achieve good performance in only indoor scenes due to the …

Simultaneous localization and mapping (SLAM) has been widely used in augmented reality
(AR), virtual reality (VR), robotics, and autonomous vehicles as the theoretical basis for …

In the evolving landscape of modern robotics, Visual SLAM (V-SLAM) has emerged over the
past two decades as a powerful tool, empowering robots with the ability to navigate and map …

Loop closure detection is essential in visual simultaneous localization and mapping systems
to recognize previously visited scenes, reducing pose and map estimates uncertainty …