Abstract: 3D single object tracking plays a crucial role in numerous applications such as autonomous driving. Recent trackers based on motion-centric paradigm perform well as they exploit motion cues ...

Abstract: Localization and navigation of vehicles using 3D point cloud maps is an important strategy in autonomous driving. In this work, we propose a new method for offline building static maps based ...

While many students find AI chatbots helpful for programming tasks, a recent study suggests a potential downside. The ...

Abstract: Accurate 3D scene generation is a cornerstone of digital twin (DT) systems. Among existing approaches, point cloud-based methods stand out for their superior accuracy and robustness. However ...

Abstract: Precise multi-point positioning during robotic assembly of small, thin, plate-like flexible components is essential for applications like electronics manufacturing, yet challenging due to ...

Abstract: Pole-like objects represent important street infrastructures for road inventory and road mapping. Existing supervised point cloud classification methods cannot correctly classify ...

Abstract: Oriented object detection in aerial images has made significant advancements propelled by well-developed detection frameworks and diverse representation approaches to oriented bounding boxes ...

Abstract: In subway tunnel environments where GPS signals cannot be received, autonomous train positioning faces significant challenges. To address this issue, this paper proposes an algorithm that ...

Abstract: Fast and accurate three-dimensional (3D) Multiple Object Detection and Tracking (3DMODT) is a critical task for autonomous vehicles to perceive their surroundings and make safe decisions.

Abstract: Generalizable 3D object reconstructionfrom single-view RGB-D images remains a challenging task, particularly with real-world data. Current state-of-the-art methods develop Transformer-based ...