Abstract: Accurate understanding of 3D objects in complex scenes plays essential roles in the fields of intelligent transportation and autonomous driving technology. Recent deep neural networks have ...

Abstract: Point cloud denoising and normal estimation are two fundamental yet dependent problems in digital geometry processing. However, both are often independently researched, leading to ...

Abstract: To cater for the growing demand of capacity, Access Point (AP) densification is a promising solution. Within an Ultra Dense Network (UDN), a mobile User Equipment (UE) can associate with one ...

Abstract: Today's network services and applications are widely distributed across multiple data centers around the world, and require timely transfer of big data between data centers to ensure the ...

Abstract: Obtaining defect-free point cloud data is challenging due to performance constraints of acquisition devices and unavoidable occlusion, making point cloud data completion critical. In recent ...

Abstract: In this work, we implement a hybrid method to utilize sufficient information by aggregating both fine-grained and globally contextual features for point cloud semantic segmentation with a ...

Abstract: Aiming at the long-distance trans-regional transmission of power data in the new power system, this paper first analyzes the suitability of 5G communication network and power business, then ...