Leap-vo: Long-term effective any point tracking for visual odometry
Visual odometry estimates the motion of a moving camera based on visual input. Existing
methods mostly focusing on two-view point tracking often ignore the rich temporal context in …
methods mostly focusing on two-view point tracking often ignore the rich temporal context in …
Dytanvo: Joint refinement of visual odometry and motion segmentation in dynamic environments
Learning-based visual odometry (VO) algorithms achieve remarkable performance on
common static scenes, benefiting from high-capacity models and massive annotated data …
common static scenes, benefiting from high-capacity models and massive annotated data …
A survey of visual SLAM methods
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 …
past two decades as a powerful tool, empowering robots with the ability to navigate and map …
Asynchronous state estimation of simultaneous ego-motion estimation and multiple object tracking for LiDAR-inertial odometry
We propose LiDAR-Inertial Odometry via Simultaneous EGo-motion estimation and Multiple
Object Tracking (LIO-SEGMOT), an optimization-based odometry approach targeted for …
Object Tracking (LIO-SEGMOT), an optimization-based odometry approach targeted for …
Imperative learning: A self-supervised neural-symbolic learning framework for robot autonomy
Multi-vehicle cooperative simultaneous LiDAR SLAM and object tracking in dynamic environments
Simultaneous localization and map** (SLAM) and moving object detection and tracking
(MODT) are two fundamental problems for autonomous driving systems. Multi-vehicle …
(MODT) are two fundamental problems for autonomous driving systems. Multi-vehicle …