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 …

Vision-based map-matching with HD map for high precision vehicle localization has gained
great attention for its low-cost and ease of deployment. However, its localization …

Visual localization in vehicle navigation remains a crucial image retrieval task to determine
the best matched image. Developing an efficient algorithm to address the localization issues …

The image-based 3D object detection task expects that the predicted 3D bounding box has
a “tightness” projection (also referred to as cuboid) to facilitate 2D-based training, which fits …

Visual Place Recognition (VPR) addresses visual instance retrieval tasks against discrepant
scenes and gives precise localization. During a traverse, the captured images (query …

In this work, we present a vision-only global localization architecture for autonomous vehicle
applications, and achieves centimeter-level accuracy and high robustness in various …

Accurate and robust localization remains a significant challenge for autonomous vehicles.
The cost of sensors and limitations in local computational efficiency make it difficult to scale …

Vision-aided localization for low-cost mobile robots in diverse environments has attracted
widespread attention recently. Although many current systems are applicable in daytime …

Many researchers have used the map-matching algorithm to leverage inadequate traditional
vehicle localization with HD maps for fast and efficient vehicle localization. The initialization …

The goal of SLAM (Simultaneous Localization and Mapping) is to estimate the trajectory of a
moving camera while building a map of its environment. Classical algorithm usually build a …