Place recognition is a critical component towards addressing the key problem of
Simultaneous Localization and Mapping (SLAM). Most existing methods use visual images; …

With its essential role in achieving full autonomy of robot navigation, place recognition has
been widely studied with various approaches. Recently, numerous point cloud-based …

With innovation in fields such as autonomous driving and augmented reality, point cloud-
based place recognition has gained significant attention. Many methods try to address this …

Human beings and animals are capable of recognizing places from a previous journey
when viewing them under different environmental conditions (eg, illuminations and …

This paper reports on a new 3D point cloud-based place recognition framework that uses SE
(3)-equivariant networks to learn SE (3)-invariant global descriptors. We discover that, unlike …

In the point-cloud-based place recognition area, the existing hybrid architectures combining
both convolutional networks and transformers have shown promising performance. They …

Place recognition gives a SLAM system the ability to correct cumulative errors. Unlike
images that contain rich texture features, point clouds are almost pure geometric information …

The paper presents a learning-based method for computing a discriminative 3D point cloud
descriptor for place recognition purposes. Existing methods, such as PointNetVLAD, are …

Place recognition plays an essential role in the field of autonomous driving and robot
navigation. Point cloud based methods mainly focus on extracting global descriptors from …

Place recognition is a fundamental topic in computer vision and robotics. It plays a crucial
role in simultaneous localization and mapping (SLAM) systems to retrieve scenes from maps …