Abstract Simultaneous Localization and Mapping (SLAM) have been widely studied over the
last years for autonomous vehicles. SLAM achieves its purpose by constructing a map of the …

Grounding 3D object affordance seeks to locate objects'" action possibilities" regions in the
3D space, which serves as a link between perception and operation for embodied agents …

Place recognition is a fundamental technology for vehicle localization. LiDAR-based
methods could work under visual appearance-changing conditions, such as season or …

Cross-view geo-localization is a critical task in various applications, such as smart city
management and disaster monitoring. Current methods typically divide a satellite image into …

When we humans recognize places from images, we not only infer about the objects that are
available but even think about landmarks that might be surrounding it. Current place …

Image geo-localization aims to locate a query image from source platform (eg, drones, street
vehicle) by matching it with Geo-tagged reference images from the target platforms (eg …

Precise estimation of global orientation and location is critical to ensure a compelling
outdoor Augmented Reality (AR) experience. We address the problem of geo-pose …

Image-based geo-localization is estimating the location of a query image by matching it to a
large amount of images in geo-tagged database. This matching task is very challenging due …

The rise of the metaverse and the increasing volume of heterogeneous 2D and 3D data
have created a growing demand for cross-modal retrieval, enabling users to query …

Understanding the perceived scene during navigation enables intelligent robot behaviors.
Current vision-based semantic SLAM (Simultaneous Localization and Mapping) systems …