TNPC: Transformer-based network for point cloud classification
Point cloud classification has emerged as a vital research area in several emerging
applications, including robotics and autonomous driving. However, discriminative feature …
applications, including robotics and autonomous driving. However, discriminative feature …
Degradation model and attention guided distillation approach for low resolution face recognition
Deep convolution neural networks (CNN) have shown their efficacy in face recognition tasks
due to their ability to extract highly discriminant face representations from face images. On …
due to their ability to extract highly discriminant face representations from face images. On …
An Intelligent Point Cloud Recognition Method for Substation Equipment Based on Multi-scale Self-attention
X Shen, Z Xu, M Wang - IEEE Transactions on Instrumentation …, 2023 - ieeexplore.ieee.org
The semantic recognition of point cloud is an important aspect of point cloud applications, it
is crucial to study the intelligent point cloud recognition method for substation equipment to …
is crucial to study the intelligent point cloud recognition method for substation equipment to …
RPEA: A Residual Path Network with Efficient Attention for 3D pedestrian detection from LiDAR point clouds
Efficiently detecting pedestrians from 3D point cloud data is a significantly challenging
perception task in numerous robotic and autonomous driving applications, primarily …
perception task in numerous robotic and autonomous driving applications, primarily …
Deep Learning-Based Target Point Localization for UAV Inspection of Point Cloud Transmission Towers
X Li, Y Li, Y Chen, G Zhang, Z Liu - Remote Sensing, 2024 - mdpi.com
UAV transmission tower inspection is the use of UAV technology for regular inspection and
troubleshooting of towers on transmission lines, which helps to improve the safety and …
troubleshooting of towers on transmission lines, which helps to improve the safety and …
DenseSphere: Multimodal 3D object detection under a sparse point cloud based on spherical coordinate
Multimodal 3D object detection has gained significant attention due to the fusion of light
detection and range (LiDAR) and RGB data. Existing 3D detection models in autonomous …
detection and range (LiDAR) and RGB data. Existing 3D detection models in autonomous …
Utilizing a Single-Stage 2D Detector in 3D LiDAR Point Cloud with Vertical Cylindrical Coordinate Projection for Human Identification
NE Budiyanta, EM Yuniarno, T Usagawa… - IEEE …, 2024 - ieeexplore.ieee.org
Exploiting sensitive human data in human visual monitoring system violates individual's
privacy. Hence, this study utilized a Light Detection and Ranging (LiDAR)-generated three …
privacy. Hence, this study utilized a Light Detection and Ranging (LiDAR)-generated three …
Unsupervised learning-based fast CU size decision for geometry videos in V-PCC
Y Li, J Huang, C Wang, H Huang - Journal of Real-Time Image Processing, 2024 - Springer
In video-based point cloud compression (V-PCC), the geometry video and attribute video
are generated through the projection of the 3D dynamic point clouds (DPCs), which can be …
are generated through the projection of the 3D dynamic point clouds (DPCs), which can be …
Geometric Edge Convolution for Rigid Transformation Invariant Features in 3d Point Clouds
SA Bello, S Alfasly, J Mao, J Lu, L Li, C Xu… - Available at SSRN … - papers.ssrn.com
Extracting rigid transformation invariant features is still a challenge on 3D point clouds
because rigid transformation changes the point coordinates, and relying on the point …
because rigid transformation changes the point coordinates, and relying on the point …